Analytics Engineer, Life Sciences Delivery Operations

📋 Description

• Author and maintain dbt models and PySpark transformations; replace ad-hoc Snowflake scripts with governed, tested code
• Design delivery endpoint configurations as code (Snowflake/S3), cadence, filters, and refresh methods
• Write production-grade Python and PySpark for data transformation and validation
• Configure AWS S3 delivery paths, Iceberg table structures, and file staging for partners
• Collaborate with platform engineering to extend Argo Workflows for automated delivery
• Implement HIPAA de-identification rules in pipelines and coordinate certification updates

🎯 Requirements

• Education: Bachelor's or Master's in Computer Science, Data Science, or related field
• 5+ years data engineering (production pipelines, dbt, Spark/PySpark) with life sciences RWD
• Production SQL proficiency in Snowflake; complex joins, CTEs, window functions, and incremental patterns
• Python and/or PySpark for data transformation; production Spark jobs
• dbt: hands-on models, tests, macros, and YAML documentation; incremental strategies
• AWS S3: file staging and delivery path management; HIPAA de-identification knowledge

🎁 Benefits

• Flexible, fully remote work environment with support to do your best work
• Exposure to senior leaders across life science and corporate engineering teams
• Clear path to grow into a player/manager role as Arcadia scales
• Be at the center of a high-impact LS data delivery pipeline
• Become the internal expert on Arcadia's LS data
• Experience with AI tools to accelerate development (e.g., Claude)