Hire Deeply Vetted Hadoop Distributed File System (HDFS) Developer

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Natig, Data Engineer

Norway
Last Updated: 14 Jul 2023

- 12+ years experience working in the IT industry; - 12+ years experience in Data Engineering with Oracle Databases, Data Warehouse, Big Data, and Batch/Real time streaming systems; - Good skills working with Microsoft Azure, AWS, and GCP; - Deep abilities working with Big Data/Cloudera/Hadoop, Ecosystem/Data Warehouse, ETL, CI/CD; - Good experience working with Power BI, and Tableau; - 4+ years experience working with Python; - Strong skills with SQL, NoSQL, Spark SQL; - Good abilities working with Snowflake and DBT; - Strong abilities with Apache Kafka, Apache Spark/PySpark, and Apache Airflow; - Upper-Intermediate English.

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Hadoop Distributed File System (HDFS)

Hadoop Distributed File System (HDFS)

Python

Python   4 yr.

Microsoft Azure

Microsoft Azure   5 yr.

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Syed S., Salesforce Developer

Pakistan
Last Updated: 4 Jul 2023

- Software Developer with 18 years of experience - Software Development Life Cycle professional background Agile/Scrum - Programming Knowledge & experience, System Migrations/Integrations, Cross Functional Skills - intermediate English - Available ASAP - No vacation plans for next 2 months

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Hadoop Distributed File System (HDFS)

Hadoop Distributed File System (HDFS)

Salesforce

Salesforce

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Artem, Scala Software Engineer with AWS Cloud

Ternopil, Ukraine
Last Updated: 4 Jul 2023
Hadoop Distributed File System (HDFS)

Hadoop Distributed File System (HDFS)

Scala

Scala

Java

Java

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Anton P., Java Team Lead / Architect

Wroclaw, Poland
Last Updated: 23 Aug 2023

- Java Team Lead and Architect with 10+ years of a demonstrated history of working in various industries, including finance, entertainment, and retail. - Proficient in Java, Scala, AWS, Jenkins, Docker, Maven, and other technologies for building high-load applications and services. - Extensive experience with Kafka Streaming applications for data transformation and aggregation. - Successfully designed and managed high-load applications utilizing Kafka for data processing and prediction. - Strong background in AWS, utilizing services like AWS Lambda, Docker, and Kubernetes to build scalable and efficient systems. - Strong experience designing and implementing technical solutions, setting up Agile teams, and mentoring developers. - Proven ability to handle multiple projects through the entire lifecycle, ensuring timely and within-budget delivery. - Experienced in conducting requirement analysis, identifying risks, and conducting mitigation action planning - Upper-Intermediate English

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Hadoop Distributed File System (HDFS)

Hadoop Distributed File System (HDFS)

Java

Java   10 yr.

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Andriy L., Data Science / Java Software Engineer

Ternopil, Ukraine
Last Updated: 4 Jul 2023
Identity Verified
Language Verified
Programming Skills Verified
CV Verified

• 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 Distributed File System (HDFS)

Hadoop Distributed File System (HDFS)

Java

Java   15 yr.

Hadoop ecosystem

Hadoop ecosystem

Python

Python   3 yr.

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Hire Hadoop Distributed File System (HDFS) engineer

FAQs about Hadoop Distributed File System (HDFS) Development

How do I hire a Hadoop Distributed File System (HDFS) developer? Arrow

Are you desperately looking for a Hadoop Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) candidates for every position. We live and breathe technical excellence, borne out of extensive industry expertise.

How quickly can I hire Hadoop Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) engineers in person. Make the right call. Bring a new Hadoop Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) 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 Distributed File System (HDFS) developers. Upstaff has a network of vetted and tested Hadoop Distributed File System (HDFS) developers. Here, you can hire web developers for a few simple coding tasks with Hadoop Distributed File System (HDFS).

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Table of Contents

How and where is Hadoop Distributed File System (HDFS) used?

  • Big Data Processing: Analyzing enormous datasets
  • Distributed Storage: Storing data across nodes
  • Data Lakes: Storing structured and unstructured data
  • Log Processing: Analyzing logs in real-time
  • Backup and Recovery: Ensuring data safety
  • Content Delivery: Distributing content efficiently
  • Data Mining: Discovering patterns in large datasets
  • IoT Data Storage: Handling Internet of Things data
  • Machine Learning: Training models on large datasets
  • Genomics Research: Analyzing genetic data

Compare Junior, Middle, Senior, and Expert/Team Lead Hadoop Distributed File System (HDFS) Developer roles

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior1-3 yearsTasks:

  • Assist in HDFS data processing
  • Basic troubleshooting
  • Implement data backups
$50,000
Middle3-5 yearsTasks:

  • Develop data pipelines
  • Optimize data storage
  • Collaborate with teams
$80,000
Senior5-8 yearsTasks:

  • Lead data architecture projects
  • Provide technical guidance
  • Quality assurance
$110,000
Expert/Team Lead8+ yearsTasks:

  • Define data strategies
  • Mentor team members
  • Drive innovation
$150,000

Quick Facts about Hadoop Distributed File System (HDFS).

  • Created in 2006, HDFS revolutionized big data storage.
  • Projects like data lakes heavily rely on HDFS technology.
  • No need to break the bank – HDFS is open source and free!
  • Spark is a popular technology often used alongside HDFS.
  • Did you know? HDFS can store petabytes of data seamlessly!

TOP Hadoop Distributed File System (HDFS) Related Technologies

  1. Apache Hadoop
  2. (Apache Software Foundation, 2006)

  3. Cloudera
  4. (Cloudera, 2008)

  5. Hortonworks Data Platform
  6. (Hortonworks, 2011)

  7. MapR
  8. (MapR Technologies, 2009)

  9. Amazon EMR
  10. (Amazon Web Services, 2009)

What are top Hadoop Distributed File System (HDFS) instruments and tools?

  • Hadoop Distributed File System (HDFS): Apache Hadoop
  • Ambari: Hortonworks
  • Oozie: Apache Software Foundation
  • ZooKeeper: Apache Software Foundation

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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.
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Maria Lapko
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