Senior Data Engineer

Responsibilities:

• Building distributed and highly parallelized Big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time
• Leveraging Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics
• Working closely with analysts and business stakeholders to develop analytics models
• Continuous delivering on Hadoop and other Big Data Platforms
• Automating processes where possible and are repeatable and reliable
• Working closely with QA team

Requirements:

• Minimum 5 years of hands-on work with Spark & Scala
• At least 7 years of professional Python development
• Minimum 5 years of working with Linux environments
• Solid background in distributed data processing engines (e.g., Spark)
• Practical knowledge of Hadoop ecosystem components (Hive, Oozie, MapReduce, etc.)
• Strong to advanced SQL proficiency
• Proven track record of designing and implementing data flows
• Expertise in Bitbucket and Git
• AWS certification or practical experience with AWS services
• Experience with unit testing frameworks and tools (JUnit 5, Mockito, Spark testing frameworks)
• Understanding of code versioning and branching strategies
• Advanced level of English (written and spoken)

Offer:

• Private medical care
• Co-financing for the sports card
• Constant support of dedicated consultant
• Employee referral program