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Andriy L., Data Science / Java Software Engineer

Ternopil, Ukraine
Last Updated: 4 Jul 2023
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• 10+ year experience with JAVA and Linux operating systems: Java 11, Spring Boot, Spring Data JPA, MySQL/MongoDB, ElasticSearch, Jenkins CI • Big Data, Data Engineering, NLP, Corpus Linguistics, ML, DL • Design and implement a distributed warehouse system (AWS migration), REST API design and cache implementation (1,000-10,000 requests/sec), Design and implement high-load microservices • Deliver special courses devoted to concurrency and prepared handbook on “Parallel and Distributed Computations” [technologies: (basics of OpenMP, MPI, CUDA, OpenCL), advanced in Java concurrency]; • Scientific projects at university related research increasing effectiveness of crypto-analysis • Upper-Intermediate English • Available Full-time • Ready to start in 2 weeks • No scheduled vacations within next 3months

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Hadoop ecosystem

Hadoop ecosystem

Java

Java   15 yr.

Python

Python   3 yr.

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Yuriy D., Data Engineer / Data Architect

Ternopil, Ukraine
Last Updated: 4 Jul 2023

- 14+ years of experience in IT; - Data Engineering and Data Architecture Experience - System-level programming, OOP and OOD, functional programming; - Profiling and optimizing code; - Writing reliable code; - Writing product documentation, supporting products; - Team working, team leading; - Strong knowledge in Mathematics and physics (over 30 scientific publications); - Mentoring skills as a senior developer;

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Hadoop ecosystem

Hadoop ecosystem

Python

Python

C++

C++

Scala

Scala

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Yaroslav M., Scala Software Engineer with Cloud & Data Engineering skills

Ternopil, Ukraine
Last Updated: 4 Jul 2023

- Professional engineer with proven ability to develop efficient solutions for complex problems, including cloud and Data projects; - Microservice architecture expertise Lightbend Reactive Architecture, Infrastructure as Code expertise in AWS CloudFormation, CI/CD (Gitlab, AWS CodePipeline), Cloud expertise - AWS; -Engineer with the ability to develop efficient solutions for complex problems, including cloud projects, AWS Services (Amazon Quicksight, EC2, S3, Glue), Databricks, Kinesis; - API development RESTful, Swagger, GraphQL, API Gateway, Microservice architecture expertise - Commercial experience in IT since 2013; - Lightbend Reactive Architecture, Infrastructure as Code expertise in AWS CloudFormation, CI/CD (Gitlab, AWS CodePipeline); - System level programming, OOP and OOD, functional programming; Stress on profiling and optimizing code, writing reliable code; - System-level programming, OOP and OOD, functional programming; - Profiling and optimizing JVM code; - Experience with product documentation and supporting products; - Upper-intermediate English; - Available ASAP.

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Hadoop ecosystem

Hadoop ecosystem

Scala

Scala

SQL

SQL

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
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Maria Lapko
Global Partnership Manager

Only 3 Steps to Hire Hadoop ecosystem Engineers

1
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
2
Meet Carefully Matched Talents
Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person.
3
Validate Your Choice
Bring new talent on board with a trial period to confirm you hire the right one. There are no termination fees or hidden costs.

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FAQs about Hadoop ecosystem Development

How do I hire a Hadoop ecosystem developer? Arrow

Are you desperately looking for a Hadoop ecosystem developer validated to your requirements and skills? Are you lacking in resources and tools to find the right developer? If yes, then you are at the right place! Because at Upstaff, the selection of the Hadoop ecosystem Developer is done professionally as per your requirement, in a short time of just a few days, from calling to the instant task of your validated developer, with all your required skills.

Where is the best place to find Hadoop ecosystem developers? Arrow

Sure enough, within the network there must be dozens, if not hundreds, of services and platforms where you can look for the Hadoop ecosystem guy you need, but just Upstaff lets you sort out the best of the best real qualified developers practically in a couple of minutes, so that you will be able to select the one whose personality will be a perfect fit to your company. This is the case when you can create a genuinely “Pizza” type of service in the field of custom software development.

How are Upstaff Hadoop ecosystem developers different? Arrow

Vetting by expert human reviewers is combined with historically curated feedback from clients and team-mates, which has enabled us to save, on average, more than 50 hours for each client team evaluating Hadoop ecosystem candidates for every position. We live and breathe technical excellence, borne out of extensive industry expertise.

How quickly can I hire Hadoop ecosystem developers through Upstaff? Arrow

Our process begins with a 30-minute discovery call: we’ll discuss your pain points, technical requirements, and team diversity. Meet Carefully Matched Hadoop ecosystem Talents. Upon your meeting confirmation, we’ll send you profiles and arrange an introduction call with the right talents for your project, within 1-3 days. Schedule a call to meet Hadoop ecosystem engineers in person. Make the right call. Bring a new Hadoop ecosystem developer on board with a trial period: confirm that the person you hired does the job right, no termination fees and no hidden fees.

How does Upstaff vet remote Hadoop ecosystem engineers? Arrow

After this introductory round, Upstaff Managers do an eval of the soft skills of the candidates before the hiring decision is approved or rejected. For the hard skills, the Upstaff Staffing Platform has a short testing session to check their Hadoop ecosystem skills or engage a senior developer to do a technical interview for more senior developers. You can reuse some of the hard and soft skills of past candidates to connect them with other jobs in the future (see below). Upstaff managers also do an eval of the talent before approving them for further work, allowing us to accelerate the work and ability to scale, but also providing information to clients on the talent pipeline. Finally, we also have a matching engine within the work mining system that matches candidates and jobs in real time.

How to hire Hadoop ecosystem developer? 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 Hadoop ecosystem developers. Upstaff has a network of vetted and tested Hadoop ecosystem developers. Here, you can hire web developers for a few simple coding tasks with Hadoop ecosystem.

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Table of Contents

How and where is Hadoop ecosystem used?

  • Log Analysis: Analyzing log data to identify patterns
  • Data Warehousing: Storing and analyzing large datasets
  • Clickstream Analysis: Tracking and analyzing user behavior
  • Recommendation Systems: Providing personalized recommendations
  • Sentiment Analysis: Analyzing and categorizing opinions
  • Fraud Detection: Identifying fraudulent activities
  • Internet of Things (IoT): Managing and analyzing IoT data
  • Image Processing: Processing and analyzing images
  • Social Media Analysis: Analyzing social media data
  • Machine Learning: Implementing machine learning algorithms

Compare Junior, Middle, Senior, and Expert/Team Lead Hadoop ecosystem Developer roles

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior1-3 years
  • Code development
  • Bug fixing
  • Basic testing
50,000
Middle3-5 years
  • Module development
  • System integration
  • Performance optimization
80,000
Senior5-8 years
  • Architecture design
  • Team mentoring
  • Project management
110,000
Expert/Team Lead8+ years
  • Strategic planning
  • Leadership
  • Client engagement
150,000

Quick Facts about Hadoop ecosystem.

  • Hadoop was born in 2005, a brainchild of Doug Cutting and Mike Cafarella.
  • Popular projects like MapReduce and HDFS thrive within the Hadoop ecosystem.
  • Entry into the Hadoop world requires a basic understanding of Java and distributed systems.
  • Spark is Hadoop’s best buddy, offering faster data processing through in-memory computation.
  • Hadoop got its name from Doug Cutting’s son’s toy elephant!

TOP Hadoop ecosystem Related Technologies

  1. Apache Hadoop
  2. Apache Spark
  3. Apache Hive
  4. Apache Pig
  5. Apache HBase
  6. Apache Kafka
  7. Apache Oozie
  8. Apache Sqoop
  9. Apache Flume
  10. Apache Ambari

What are top Hadoop ecosystem instruments and tools?

  • HDFS: Distributed file system, Apache, 2006
  • MapReduce: Parallel processing, Apache, 2004
  • Pig: Data flow language, Apache, 2008
  • Hive: Data warehouse, Apache, 2010
  • Spark: In-memory processing, Apache, 2014
  • HBase: NoSQL database, Apache, 2010
  • Sqoop: Data transfer, Apache, 2011
  • Oozie: Workflow scheduler, Apache, 2009
  • ZooKeeper: Coordination service, Apache, 2011
  • Flink: Stream processing, Apache, 2016

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Talk to Our Talent Expert

Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Manager
Maria Lapko
Global Partnership Manager