Description

You will develop big data applications within the Hadoop ecosystem and drive DevOps and data engineering best practices.

This role is hybrid.

Responsibilities

• Develop big data applications leveraging Hadoop, NoSQL, In-memory Data Grids, Kafka, Spark, and Ab Initio.
• Build and support Jenkins and Cloudbees CI/CD pipelines, using Sonarqube for code quality analysis.
• Create, manage, and execute test cases and scripts to identify process bottlenecks.
• Document data asset lineage in enterprise metadata repositories and implement data quality rules.
• Identify repeatable engineering processes to develop common reusable tools and frameworks.

Required Skills

• Programming experience in Scala, Java, or Python.
• 2+ years of hands-on experience with shell scripting, complex SQL queries, Hive scripts, Hadoop commands, and Git.
• Experience with ETL, data warehousing, or data lake environments.
• Ability to write abstracted, reusable code components.
• Bachelor's degree in a quantitative field (Engineering, CS, Statistics, Econometrics) or 4-5 years of IT experience in lieu of a degree.
• Strong understanding of functional and non-functional requirements.
• Experience working in an agile development process including backlog grooming and code reviews.

Preferred Skills

• Familiarity with Ab Initio tools (GDG, Co>Operating System, Metadata Hub, etc.).
• Experience with Hortonworks/Cloudera, ZooKeeper, Oozie, and Kafka.
• Exposure to AWS data analytics services and Collibras data management tools.

Key Skills

Education

Bachelor's degree