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126 Available Apache Kafka Talents

🔥 Mykhaylo R. DevOps/SRE/Lead System Administrator

NetOps and SysOps, DevOps

- Over 20 years in IT with a master's degree in Cybernetics - Proficient in Ansible: Extensive experience in deploying and managing Ansible-driven infrastructure, particularly highlighted in roles as SRE/Architect (Aug 2018 – Present) and Senior DevOps Engineer/Lead Sysadmin (Aug 2020 – May 2021), where Ansible was pivotal in scaling a learning platform from 1,000 to over 100,000 students and in key migration projects. - Expertise in Windows Environments: Demonstrated strong skills in managing Windows environments, especially as an SRE/Architect (Aug 2018 – Present) and CTO (2013 – Mar 2022), involving Windows AD+MSSQL backoffice management and ITIL Service Management framework implementation on Windows platforms. - Versatile IT Roles with Ansible and Windows: Across various roles including IT Service Manager, Senior DevOps Engineer, and CTO, consistently applied Ansible and Windows technologies in large-scale infrastructure projects and day-to-day operations, showing versatility and depth in these areas. - Managing the growth of the learning platform from 1,000+ to 100k+ active students - ITIL v3 Foundations Certificate - More than 5 years of experience in leading ITIL Service Management capability and implementing end-to-end ITIL Service Management framework - Strong experience in using ServiceNow and Jira Service Desk for ITSM - Experienced IT/Telecom Specialist - UNIX and UNIX-Like OS (FreeBSD, Linux, SunOS, MacOS X) background - Over 20 years of Windows/windows server family. From NT4.0 /win3.1 up to Server2019. As well as upgrading Up to 15 years with server HW, and 13 years with storage solutions - Infrastructure problem-solver with a strong view on reliability, performance, and disaster recovery - Fluent English

Apache Kafka

Apache Kafka

Bash

Bash   10 yr.

Shell Scripts

Shell Scripts   10 yr.

MySQL

MySQL   10 yr.

Ansible

Ansible

Ansible Playbook

Ansible Playbook

english

C1 (Advanced) English

seniority

Senior (5-10 years)

location

Ukraine

Identity Verified
Language Verified
Programming Skills Verified
CV Verified

Last Updated: 20 Feb 2024

ID: 300-039-723

Andrey Sh. Product Manager/Owner

Project Manager

- Experienced B2B Product Manager dedicated to delivering innovative products that effectively address customer pain points and drive revenue growth for businesses. - Skilled in managing a diverse range of projects, spanning from small-scale B2B/B2C web services and mobile applications to large-scale Enterprise systems. - Committed to leveraging expertise in product development, strategic planning, and cross-functional collaboration to drive successful outcomes and enhance the overall customer experience. - Extensive working experience in Product Management; - Extensive working experience in Business Analysis; - In-depth professional experience in defining and prioritization the development of new or enhanced data products in conjunction with business users and other stakeholders; - Extensive hands-on experience in alignment of needs with stakeholders; - Extensive working experience in agile practices and methodologies - In-depth professional experience in managing the product backlog, planning, and prioritization of product/feature development; - Strong ability to prioritize, focus, and organize; - Proficient in various aspects of managing a multi-disciplinary product development team - Excellent English language and communication skills, - Able to effectively manage shifting priorities and handle unexpected changes

Apache Kafka

Apache Kafka

Project Management

Project Management   5 yr.

Business Analysis

Business Analysis   5 yr.

Agile

Agile   5 yr.

english

C1 (Advanced) English

seniority

Senior (5-10 years)

location

Poland, Wroclaw

Last Updated: 30 Jan 2024

ID: 700-129-180
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Find Apache Kafka Developers Your Way
Check 1-3 Days before you see the first candidates available to start within 1-2 weeks (vs 1-2 months average hiring period)
Check You get pre-screened, vetted, properly selected candidates matching your requirements
Check No long-term commitment is required
Check Pre-defined termination, no issues with employee termination

Meet Our Team

We believe in fostering a transparent and inclusive environment where creativity thrives, empowering both clients and candidates to achieve their full potential.

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Upstaff Model Comparison

Upstaff

Easier

You review profiles & meet only few pre-screened finalists to decide who will be join your team

Faster

Upstaff gives 1-3 Days before you see the first candidates available to start within 1-2 weeks

More Scalable

Together we identify project requirements and ideal candidate profile

Supervision

Engineer gets on-boarded. Upstaff team keeps supervising

Freelancers / Upwork

Item More Difficult
Item Less Reliable

In-house Recruitment

Item Slower
Item Less Flexible

Outsourcing Company

Item Less Scalable, Expensive
Item Professionalism & Quality

External Recruiter

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E-commerce traffic management system

Company: NDA
Industry: E-commerce Location: Germany
802.1X

802.1X

Adobe CQ

Adobe CQ

AEM 6.4

AEM 6.4

Agile Project Management

Agile Project Management

Airtable

Airtable

About the client

The client is the key provider of smart web traffic management solutions, partnering with 52+ businesses across Europe — from enterprise companies to government applications.

Challenge

As the client has already worked with high volumes of data, the goal was to grow the web traffic, expand the network of partners, and transfer the project into an offline mode. It meant putting higher pressure on the network, which threatened to disrupt the entire system.

Solution

Our engineers discovered why servers crashed, fixed bugs that influenced web servers’ performance, and dealt with issues that interrupted the proper functioning of databases.

Key outcomes
  • Engineers updated the servers’ environment, infrastructure, and architecture of the database system, which let the system handle higher volumes of data
  • The traffic grew x3 in 4 months, which allowed the client to process over 5 million transactions daily

Landscape management solutions

Company: NDA
Industry: Landscape services Location: USA
Adobe Creative Suite

Adobe Creative Suite

Adobe CQ

Adobe CQ

Adobe After Effects

Adobe After Effects

Adobe Acrobat X

Adobe Acrobat X

Adobe Experience Manager (AEM)

Adobe Experience Manager (AEM)

Adobe indesign

Adobe indesign

About the client

The company has been serving facility professionals who manage various commercial properties since 1995. They offer a complex solution that covers site planning, mapping, and bonding, adding value by simplifying all ground management into one contract.

Challenge

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

Solution

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

Key outcomes

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

  • As our engineers achieved the goal in time, it gave space to move to the backlog tasks and develop new features
  • The team started preparing the system for switching to React, moving towards a yearly goal

French Luxury Brand

Company: NDA
Industry: Fashion Location: Paris
AbodeXD

AbodeXD

Active Directory

Active Directory

Active model serializer

Active model serializer

Active Server Pages (ASP)

Active Server Pages (ASP)

Adapt-Framework

Adapt-Framework

Ad-hoc testing

Ad-hoc testing

Actix Web

Actix Web

CSS

CSS

About the client

Being a world-class fashion house, our client offers chic clothing, bags, and jewelry, putting everyone who touches the brand in the lap of luxury. Headquartered in France, the company is among founding fathers of haute couture — one-of-a-kind, impeccable design.

Challenge

The company operates in 25 states with hundreds of stores and millions of customers worldwide. Enlarging the services, the client was lacking experienced PWA developers to refine its Magneto extensions on a regional website.

Solution

In just a week, developers kicked off the project and started working with Magento 2 and PWA Studio. The ultimate goal was to implement and develop custom modules and extensions. After six months of cooperation, the team presented shiny custom modules developed from scratch.

Key outcomes

As engineers worked on the project, the regional website performance along with the user engagement have increased.

  • The usability of the website was refined, which increased conversion rates by 10%
  • Overall user engagement grew by 35% while drop offs rate got lower
  • The brand got time to develop in other directions, continuing to grow its services
Introduction
How to Assess Apache Kafka Developer Skills
Quick Facts about Apache Kafka
How and Where is Airtable used
Apache Kafka Related Tech:
Using Apache Kafka: What are Pros & Cons ?
Top Apache Kafka Instruments and Tools
Difference between Junior, Middle, Senior, and Expert/Team Lead, Front-End, Database Apache Kafka Developers
Let's consider hard & soft skills of Apache Kafka Developer
Common Cases When Apache Kafka Faces Issues
Where to Find Apache Kafka Developers
Hire Apache Kafka Developer - What to Expect
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Conclusion
Introduction
How to Assess Apache Kafka Developer Skills
Quick Facts about Apache Kafka
How and Where is Airtable used
Apache Kafka Related Tech:
Using Apache Kafka: What are Pros & Cons ?
Top Apache Kafka Instruments and Tools
Difference between Junior, Middle, Senior, and Expert/Team Lead, Front-End, Database Apache Kafka Developers
Let's consider hard & soft skills of Apache Kafka Developer
Common Cases When Apache Kafka Faces Issues
Where to Find Apache Kafka Developers
Hire Apache Kafka Developer - What to Expect
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Conclusion
Introduction
How to Assess Apache Kafka Developer Skills
Quick Facts about Apache Kafka
How and Where is Airtable used
Apache Kafka Related Tech:
Using Apache Kafka: What are Pros & Cons ?
Top Apache Kafka Instruments and Tools
Difference between Junior, Middle, Senior, and Expert/Team Lead, Front-End, Database Apache Kafka Developers
Let's consider hard & soft skills of Apache Kafka Developer
Common Cases When Apache Kafka Faces Issues
Where to Find Apache Kafka Developers
Hire Apache Kafka Developer - What to Expect
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Conclusion

Introduction

Are you considering expanding your team with top-notch developers? Hiring Apache Kafka developer might be the game-changer your project needs. In this comprehensive guide, we explore the intricacies of finding and hiring skilled Apache Kafka developers.

How to Assess Apache Kafka Developer Skills

Ensuring you have the right developer on board involves a thorough assessment. Delve into the details of technical interviews, evaluating real-world project experience, and choosing the developer whose skills align with your project requirements.

TOP 8 Facts about Apache Kafka

Overview: Apache Kafka, a distributed streaming platform, is a force in real-time data processing. With scalability, fault tolerance, and durability at its core, Kafka reshapes data streaming landscapes.

1. Birth of Kafka: Conceived in 2011 by LinkedIn engineers Jay Kreps, Neha Narkhede, and Jun Rao, Kafka revolutionized data handling. Originating from the need for a scalable, fault-tolerant system, Kafka’s birth heralded a new era in distributed streaming.

2. Streaming at Scale: Kafka employs a publish-subscribe model, enabling seamless communication across distributed systems. The methodology’s success lies in its ability to handle massive data flows with low latency and high throughput.

3. Evolution through Versions: Kafka’s evolution is marked by significant version releases. Noteworthy milestones include Version 0.8 (2013), introducing Kafka’s first stable version, and Version 2.8 (2021), which strengthened Kafka’s position with added features and optimizations.

4. Brokers and Partitions: Kafka’s architecture revolves around brokers that manage partitions, providing resilience and scalability. This design choice ensures that Kafka seamlessly adapts to varying workloads and sustains high data volumes.

5. Fault Tolerance: Kafka’s replication factor mechanism ensures fault tolerance by creating copies of data across multiple brokers. This feature safeguards against data loss, contributing to Kafka’s reputation for robustness.

6. Ecosystem Integration: Kafka integrates seamlessly with diverse ecosystems, fostering compatibility with popular programming languages, databases, and analytics tools. This adaptability cements Kafka’s role in versatile data processing scenarios.

7. Kafka Streams API: The introduction of the Kafka Streams API empowered developers to build robust stream processing applications directly within the Kafka ecosystem. This streamlined approach simplifies data processing pipelines.

8. Open Source Community: Kafka’s success is amplified by its thriving open-source community. Developers globally contribute to Kafka’s growth, expanding its capabilities and ensuring continuous innovation.

In essence, Apache Kafka isn’t just a platform; it’s a dynamic force reshaping the contours of real-time data processing, standing as a testament to the prowess of distributed streaming architectures.

How and where is Apache Kafka used?

Overview: Apache Kafka, a data streaming powerhouse, finds its technological mettle woven into the fabric of real-time data processing landscapes, orchestrating seamless communication across diverse domains.

  • Financial Transactions: Kafka fortifies financial institutions by facilitating real-time transaction processing and ensuring data integrity, reducing latency and enabling secure monetary transactions.
  • Log Aggregation: In massive server environments, Kafka emerges as the linchpin for log aggregation, consolidating logs from disparate sources to simplify debugging and enhance system visibility.
  • IoT Infrastructure: Kafka’s scalability makes it the backbone of IoT ecosystems, efficiently handling the torrent of data generated by interconnected devices, ensuring smooth communication and data flow.
  • Event Sourcing: Kafka excels in event sourcing architectures, capturing every state-changing event in the sequence it occurs, ensuring a comprehensive and accurate historical record for applications.
  • Monitoring and Alerting: Kafka’s ability to handle high throughput data streams makes it indispensable for monitoring and alerting systems, ensuring timely notifications based on real-time insights.
  • Microservices Communication: Kafka seamlessly connects microservices in distributed architectures, providing a reliable and fault-tolerant communication channel, fostering scalability and flexibility.
  • Big Data Processing: Kafka plays a pivotal role in big data processing, serving as a high-throughput, fault-tolerant buffer that efficiently feeds data into processing frameworks like Apache Spark and Apache Flink.
  • Supply Chain Optimization: Kafka optimizes supply chain processes by facilitating real-time tracking, monitoring, and analysis, enhancing visibility and enabling agile decision-making in dynamic supply chain environments.
  • Real-time Analytics: Organizations leverage Kafka to power real-time analytics platforms, enabling the extraction of actionable insights from streams of data, leading to informed decision-making.
  • Customer Engagement Platforms: Kafka underpins customer engagement systems by ensuring the seamless flow of data, enabling personalized and real-time interactions across various touchpoints.
  • Healthcare Data Management: In the healthcare sector, Kafka supports real-time data streaming for patient monitoring, ensuring timely insights and interventions, and enhancing overall patient care.
  • Media Streaming: Kafka’s robust architecture finds application in media streaming services, handling vast amounts of data to provide uninterrupted and high-quality streaming experiences to users.

Note: The versatility of Apache Kafka extends beyond these cases, with its adoption growing across industries for diverse real-time data processing needs.

Top 7 Apache Kafka Related Technologies:

  1. Kafka Streams API

    As Kafka’s native stream processing library, the Streams API empowers developers to concoct mesmerizing data pipelines. It seamlessly integrates with Kafka’s robust architecture, allowing developers to craft complex streaming applications with ease. Dive into the stream, where real-time magic happens!

  2. Confluent Platform

    Confluent, the brainchild of Kafka’s creators, extends Kafka’s capabilities with the Confluent Platform. This toolkit provides a trove of enhancements, from data integration and connectors to the Confluent Control Center, a cockpit for managing Kafka clusters. It’s like Kafka on steroids, without the gym membership.

  3. Kafka Connect

    Kafka Connect acts as the bridge between Kafka and external data sources/sinks. With a vast array of connectors, it facilitates seamless data flow, allowing you to plug into various systems without breaking a sweat. It’s the universal translator for your data, connecting Kafka to the world.

  4. Avro

    Avro, the binary serialization system, adds a dash of efficiency to Kafka. With Avro, your data takes a sleek, compact form, ensuring faster transmission and reduced storage costs. It’s the Marie Kondo of data serialization, keeping things tidy and sparking joy in your Kafka streams.

  5. Apache Flink

    For those craving real-time stream processing nirvana, Apache Flink joins forces with Kafka. Flink glides through Kafka streams, offering state-of-the-art processing capabilities. It’s like having a ninja at your data’s disposal, swiftly executing computations with finesse.

  6. Schema Registry

    The Schema Registry, Kafka’s guardian of data schemas, ensures order in the chaotic world of evolving data structures. It safeguards compatibility, allowing you to upgrade your data without causing pandemonium. It’s the Kafka librarian, preserving the harmony of your data melodies.

  7. KSQL

    KSQL, the SQL engine for Kafka, transforms your data processing journey into a linguistic symphony. With a familiar SQL interface, it lets you query and manipulate streams effortlessly. It’s like having a conversation with your data, where SQL is the language of love.

Pros & Cons of Apache Kafka

Overview: Apache Kafka, the juggernaut of distributed streaming, boasts unmatched scalability and fault tolerance, but it’s not devoid of challenges.

Pros:

  • Scalability: Kafka’s architecture effortlessly scales horizontally, accommodating increasing data loads without breaking a sweat. It’s the Hercules of data streams, growing stronger with every challenge.
  • High Throughput: With its publish-subscribe model, Kafka achieves stellar throughput, ensuring data races through the system with minimal latency. It’s the Usain Bolt of data processing, leaving competitors in the dust.
  • Durability: Kafka’s replication mechanism guarantees data durability, preventing loss even in the face of hardware failures. It’s the Fort Knox of data storage, ensuring your information remains impervious to calamities.
  • Flexibility: Kafka’s compatibility with various programming languages and frameworks provides unparalleled flexibility. It’s the polyglot of data, effortlessly adapting to diverse tech ecosystems.
  • Real-time Processing: Kafka’s ability to process data in real-time empowers applications with up-to-the-moment insights. It’s the live broadcast of data, delivering information with the immediacy of breaking news.
  • Ecosystem Integration: Kafka seamlessly integrates with a plethora of tools and frameworks, forming a robust ecosystem. It’s the chameleon of the tech world, blending harmoniously with diverse environments.
  • Community Support: A vibrant open-source community ensures continuous improvement and support. It’s the collaborative orchestra, where developers worldwide compose the symphony of Kafka’s evolution.
  • Reliability: Kafka’s track record for reliability solidifies its standing as a stalwart in data streaming. It’s the trusted companion, navigating the tumultuous waters of data with unwavering precision.

Cons:

  • Complexity: Setting up and configuring Kafka can be intricate, demanding a nuanced understanding of its architecture. It’s the intricate puzzle, requiring adept hands to piece together seamlessly.
  • Operational Overhead: Managing Kafka clusters involves operational complexities, demanding vigilant monitoring and maintenance. It’s the high-maintenance pet, requiring constant care to thrive.
  • Learning Curve: Mastering Kafka’s intricacies necessitates a steep learning curve for new users. It’s the challenging climb, rewarding those who persevere with the panoramic view of distributed streaming.
  • Storage Costs: The durability afforded by replication comes at the cost of increased storage requirements. It’s the spacious vault, safeguarding data but demanding ample room.
  • ZooKeeper Dependency: Kafka relies on ZooKeeper for cluster management, introducing an additional layer of complexity. It’s the silent partner, working behind the scenes but adding a layer of orchestration.

Top Apache Kafka Instruments and Tools

  • Kafka ManagerA web-based UI tool, Kafka Manager, emerged from the need to simplify Kafka cluster monitoring. Developed by Yahoo engineers, it allows effortless management and monitoring of Kafka clusters. It’s the Swiss Army knife for Kafka administrators, ensuring smooth sailing in the Kafka seas.
  • Kafka ToolKafka Tool, a cross-platform GUI application, caters to Kafka developers and administrators. Born out of the necessity for a user-friendly interface, it provides features for managing topics, consumers, and more. It’s the go-to companion, streamlining Kafka management with a sleek interface.
  • Confluent Control CenterThe brainchild of Confluent, the company founded by Kafka’s creators, the Control Center is a comprehensive management tool. It offers real-time metrics, monitoring, and management capabilities for Kafka clusters. It’s the mission control for Kafka, providing insights and control at your fingertips.
  • Schema RegistrySchema Registry, a pivotal part of the Confluent Platform, manages the evolution of schemas in a Kafka ecosystem. It ensures data compatibility, allowing seamless evolution of data structures. It’s the custodian of data integrity, preserving the harmony of evolving schemas.
  • KSQLKSQL, born from the Confluent platform, injects SQL into Kafka streams. It enables developers to query, transform, and process streaming data using familiar SQL syntax. It’s the polyglot of data languages, bridging the gap between relational and streaming paradigms.
  • BurrowCreated by LinkedIn, Burrow monitors Kafka consumer lag, aiding in the identification of potential issues. It’s the vigilant guardian, ensuring that Kafka consumers keep pace with the data influx. Burrow’s open-source nature solidifies its role as a sentinel in the Kafka landscape.
  • Kafka ConnectKafka Connect, a framework included in Apache Kafka, simplifies the integration of external systems with Kafka. It acts as a bridge, enabling seamless data transfer between Kafka and various sources/sinks. It’s the data highway, connecting Kafka to the expansive world of data.
  • DebeziumDebezium, a CDC (Change Data Capture) tool for Kafka, captures and streams database changes. It provides real-time updates, ensuring Kafka consumers stay in sync with evolving databases. It’s the herald of data changes, delivering updates with the precision of a maestro’s baton.
  • Kafka StreamsKafka Streams, the native stream processing library of Kafka, empowers developers to build real-time applications. It seamlessly integrates with Kafka, enabling the creation of robust streaming pipelines. It’s the alchemist’s toolkit, turning Kafka into a transformative force in real-time data processing.
  • StrimziStrimzi, an open-source project, simplifies the deployment and management of Kafka on Kubernetes. It’s the enabler of Kafka’s journey into containerized environments, ensuring a smooth transition into the Kubernetes ecosystem.

Difference between Junior, Middle, Senior, Expert/Team Lead, Apache Kafka Data Engineer, and ETL Developer

Role Experience Task Complexity Average Salary (USD/year) Performance Team Collaboration
Junior Data Engineer 0-2 years Basic data processing, troubleshooting, and support. $50,000 – $70,000 Individual contributions to small projects. Limited collaboration within the team.
Middle Data Engineer 2-5 years Developing and optimizing data pipelines, database management. $70,000 – $90,000 Independently manage mid-sized projects. Collaborate with team members on project tasks.
Senior Data Engineer 5-8 years Architecting data solutions, mentoring team members. $90,000 – $120,000 Lead and manage complex data projects. Mentor and collaborate closely with junior and middle engineers.
Expert/Team Lead Data Engineer 8+ years Strategic planning, project management, team leadership. $120,000 – $150,000+ Lead multiple teams, set technical direction. Collaborate with management on strategic initiatives.
Apache Kafka Data Engineer Varies Expertise in Apache Kafka, stream processing. Varies Varies Varies
ETL Developer with Apache Kafka Varies Proficiency in ETL tools, hands-on experience with Apache Kafka. Varies Varies Varies

Hard Skills of an Apache Kafka Developer

Junior Apache Kafka Developer

Overview: Junior Kafka Developers focus on foundational skills for understanding and contributing to Kafka projects.

Skills:

  • Basic understanding of Kafka architecture and components
  • Experience with Kafka command-line tools
  • Ability to configure and manage Kafka topics
  • Understanding of Kafka producer and consumer APIs
  • Basic knowledge of stream processing using Kafka Streams

Middle Apache Kafka Developer

Overview: Middle Kafka Developers possess advanced skills for designing and optimizing Kafka data pipelines.

Skills:

  • Advanced Kafka configuration and optimization
  • Experience with Kafka Connect for integration with external systems
  • Proficient in troubleshooting Kafka performance issues
  • Design and implementation of Kafka security features
  • Integration of Kafka with other big data technologies
  • Knowledge of schema management using Schema Registry

Senior Apache Kafka Developer

Overview: Senior Kafka Developers take on leadership roles, guiding complex Kafka projects and ensuring scalability.

Skills:

  • Leadership in designing and implementing large-scale Kafka solutions
  • Expertise in Kafka cluster management and optimization
  • Architecting and implementing Kafka disaster recovery solutions
  • Implementation of Kafka authorization and authentication
  • Deep understanding of Kafka internals
  • Performance tuning of Kafka brokers and consumers
  • Experience with Kafka on Kubernetes (Strimzi)
  • Implementation of Kafka mirroring and replication

Expert/Team Lead Apache Kafka Developer

Overview: Expert/Team Lead Kafka Developers are strategic leaders, shaping the direction of Kafka initiatives.

Skills:

  • Strategic planning for enterprise-level Kafka implementations
  • Team leadership and mentoring
  • Integration of Kafka with cloud services (AWS, Azure, GCP)
  • Implementation of Kafka in microservices architectures
  • Development of custom Kafka tools and utilities
  • Expertise in Kafka-based event sourcing patterns
  • Implementation of Kafka tiered storage
  • Experience with Kafka in hybrid cloud environments
  • Implementation of Kafka monitoring and alerting
  • Implementation of Kafka encryption and data masking
  • Knowledge of Kafka ecosystem tools (KSQL, Burrow, etc.)

Apache Kafka Data Engineer

Overview: Data Engineers with Apache Kafka expertise focus on creating scalable and efficient data pipelines.

Skills:

  • Design and implementation of real-time data streaming with Kafka
  • Integration of Kafka with data storage solutions (Hadoop, Cassandra)
  • Experience with Kafka cluster deployment and management
  • Optimization of data processing using Kafka
  • Development of custom Kafka connectors

Extract, Transform, and Load (ETL) with Apache Kafka

Overview: ETL Developers leveraging Apache Kafka specialize in efficient data movement and transformation.

Skills:

  • Design and implementation of ETL processes using Kafka
  • Integration of Kafka with data warehousing solutions (e.g., Snowflake)
  • Implementation of data transformation using Kafka Streams
  • Optimization of ETL workflows for large-scale data
  • Development of real-time data integration solutions
  • Experience with CDC (Change Data Capture) using Kafka (Debezium)
  • Implementation of error handling and data reconciliation in ETL
  • Integration of ETL with Kafka monitoring tools
  • Implementation of idempotent ETL processes with Kafka
  • Experience with ETL orchestration tools (e.g., Apache NiFi)

Soft Skills of an Apache Kafka Developer

Overview:

Soft skills are crucial for effective

Common Cases When Apache Kafka Faces Issues

1. Disk Space Exhaustion

Kafka relies heavily on disk storage for maintaining logs. In cases where disk space is insufficient, Kafka may encounter issues in writing and managing logs, leading to system instability.

2. Network Partitions

Network partitions can disrupt communication between Kafka brokers and Zookeeper nodes. In such scenarios, Kafka may struggle to maintain consensus, impacting the overall reliability and performance of the system.

3. Misconfigured Replication Factors

Incorrectly configured replication factors can result in data inconsistencies and unavailability. If the replication factor is set too low or misconfigured, Kafka may fail to ensure data durability and fault tolerance.

4. Insufficient Memory Allocation

If Kafka brokers do not have adequate memory allocation, it can lead to performance degradation and increased disk I/O. This may result in delayed processing and potential data loss during high-throughput scenarios.

5. Zookeeper Instabilities

Zookeeper plays a critical role in Kafka’s coordination and metadata management. Instabilities or misconfigurations in the Zookeeper ensemble can impact Kafka’s functionality, leading to connectivity issues and service disruptions.

Where to Find Apache Kafka Developers

Explore the various platforms available for hiring Apache Kafka developers, from popular online platforms to specialized agencies. Learn about the benefits each option offers to streamline your hiring process.

Hire Apache Kafka Developer – What to Expect

Get insights into what to expect when hiring an Apache Kafka developer, including timelines for project completion and continuous support post-deployment. Make informed decisions for a smooth development journey.

Common Mistakes to Avoid

Avoiding pitfalls in the hiring process is crucial for success. Learn about common mistakes, such as neglecting communication skills and ignoring cultural fit, to ensure a seamless collaboration.

Ensuring a Successful Collaboration

Setting the stage for success involves clear expectations and regular communication. Explore the strategies for ensuring a successful collaboration with your hired Apache Kafka developer.

Case Studies

Read real-life case studies showcasing successful projects powered by Apache Kafka. Dive into client testimonials and understand how Apache Kafka developers have contributed to project success.

Conclusion

In conclusion, hiring Apache Kafka developer is a strategic move for any development project. By understanding the key skills, avoiding common mistakes, and fostering a successful collaboration, you set the stage for a seamless and efficient development journey.

FAQs about Hiring Apache Kafka Developers

How to choose the right developer? Arrow

Choosing the right Apache Kafka developer involves assessing skills, experience, and cultural fit. Look for a developer whose expertise aligns with your project requirements.

What is the average cost of hiring? Arrow

The cost of hiring a Apache Kafka developer varies based on experience and location. On average, rates range from $35 to $50 per hour, with additional costs for specialized skills.

Ensuring code security Arrow

Apache Kafka developers should prioritize code security. Ensure your developer follows best practices, conducts regular security audits, and stays updated on the latest security trends.

Handling scalability issues Arrow

Scalability is crucial for successful projects. Hire a developer with experience in building scalable applications and addressing potential bottlenecks in Apache Kafka.

Resolving conflicts in development Arrow

Conflicts may arise during the development process. Effective communication and a collaborative approach are key to resolving conflicts and maintaining a positive working relationship.

How to hire Apache Kafka developers? Arrow

If recruiting services and job boards are not your 1st option, you may want to consider a client-oriented service like Upstaff to find & hire Apache Kafka developers. Upstaff has a network of vetted and tested Apache Kafka engineers. Here you can hire web developers for a few simple coding tasks with Apache Kafka.

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Henry Akwerigbe
Henry Akwerigbe
This is a super team to work with. Through Upstaff, I have had multiple projects to work on. Work culture has been awesome, teammates have been super nice and collaborative, with a very professional management. There's always a project for you if you're into tech such Front-end, Back-end, Mobile Development, Fullstack, Data Analytics, QA, Machine Learning / AI, Web3, Gaming and lots more. It gets even better because many projects even allow full remote from anywhere! Nice job to the Upstaff Team 🙌🏽.
Vitalii Stalynskyi
Vitalii Stalynskyi
I have been working with Upstaff for over a year on a project related to landscape design and management of contractors in land design projects. During the project, we have done a lot of work on migrating the project to a multitenant architecture and are currently working on new features from the backlog. When we started this project, the hiring processes were organized well. Everything went smoothly, and we were able to start working quickly. Payments always come on time, and there is always support from managers. All issues are resolved quickly. Overall, I am very happy with my experience working with Upstaff, and I recommend them to anyone looking for a new project. They are a reliable company that provides great projects and conditions. I highly recommend them to anyone looking for a partner for their next project.
Владислав «Sheepbar» Баранов
Владислав «Sheepbar» Баранов
We've been with Upstaff for over 2 years, finding great long-term PHP and Android projects for our available developers. The support is constant, and payments are always on time. Upstaff's efficient processes have made our experience satisfying and their reliable assistance has been invaluable.
Roman Masniuk
Roman Masniuk
I worked with Upstaff engineers for over 2 years, and my experience with them was great. We deployed several individual contributors to clients' implementations and put up two teams of upstaff engineers. Managers' understanding of tech and engineering is head and shoulders above other agencies. They have a solid selection of engineers, each time presented strong candidates. They were able to address our needs and resolve things very fast. Managers and devs were responsive and proactive. Great experience!
Yanina Antipova
Yanina Antipova
Хочу виразити велику подяку за таку швидку роботу по підбору двох розробників. Та ще й у такий короткий термін-2 дні. Це мене здивувало, адже ми шукали вже цілий місяць. І знайдені кандидати нам не підходили Це щось неймовірне. Доречі, ці кандидати працюють у нас і зараз. Та надать приклад іншим працівникам. Гарного дня!)
Наталья Кравцова
Наталья Кравцова
I discovered an exciting and well-paying project on Upstaff, and I couldn't be happier with my experience. Upstaff's platform is a gem for freelancers like me. It not only connects you with intriguing projects but also ensures fair compensation and a seamless work environment. If you're a programmer seeking quality opportunities, I highly recommend Upstaff.
Volodymyr
Volodymyr
Leaving a review to express how delighted I am to have found such a great side gig here. The project is intriguing, and I'm really enjoying the team dynamics. I'm also quite satisfied with the compensation aspect. It's crucial to feel valued for the work you put in. Overall, I'm grateful for the opportunity to contribute to this project and share my expertise. I'm thrilled to give a shoutout and recommendation to anyone seeking an engaging and rewarding work opportunity.

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