Staff Software Data Engineer

• Review functional requirements, create technical designs and specifications, and implement with coding and testing.
• Size work for medium to large complexity and manage timelines and delivery.
• Design and develop software using data engineering technologies.
• Spend approximately 90% of time on designing, coding, testing, and supporting production systems, including on-call responsibilities.
• Identify and resolve defects or bugs during testing, pre-production, production, and post-release patching.
• Collaborate cross-functionally with product management, other engineering teams, and business units to drive outcomes.
• Apply Agile Development, SCRUM, or Extreme Programming practices as part of delivery.

• 7+ years developing data engineering pipelines using Python, PySpark, Spark, SQL, DataBricks, AWS, Elastic Search, and Kafka.
• 7+ years working on Big Data technologies.
• BS/MS in computer science or equivalent work experience.
• Strong experience with Python and Spark, including the ability to understand and work within a large existing codebase.
• Experience across the entire Software Development Life Cycle (SDLC).
• Demonstrated ability to build and support large-scale enterprise data engineering pipelines and data feature development.
• Demonstrated operational excellence and engineering focus, including production support via quarterly on-call rotations to monitor systems and resolve production errors and incidents.
• Demonstrated communication skills, including the ability to explain complex technical topics to both technical and non-technical audiences.
• Strong understanding of the software design and architecture process.
• Experience with unit testing and Test-Driven Development (TDD).

Key Technologies

• Python
• PySpark
• Spark
• SQL
• DataBricks
• AWS
• Elastic Search
• Kafka