Staff Data Engineer
$175,000–$175,000 year
HybridNew York, United States
Job Summary
Build, release, and maintain high-quality ELT and streaming pipelines with a focus on correctness, observability, and performance using Dagster, Airflow, and DBT. Own significant areas of the Snowflake data warehouse, designing performant schemas and maintaining clear documentation of data definitions and lineage. Resolve critical data issues independently and contribute to architectural decisions with data-driven recommendations. Support analytics delivery through Hex and AI Agents while helping the team level up via documentation and continuous improvement initiatives. Participate in the on-call rotation to ensure data availability and pipeline health.
Required Qualifications
- Bachelor's degree in Computer Science, Mathematics, or a related technical discipline, or equivalent practical experience
- 7+ years of experience in Data, with at least 4 years in a Data Engineering role
- Deep expertise in analytical use cases of SQL, including CTEs, window functions, aggregation patterns, and performance tuning techniques such as partitioning and clustering
- Strong proficiency in Python, including experience with common data engineering libraries
- Hands-on experience with a modern data stack
- Demonstrated ability to take ownership of loosely-defined problems, breaking them into well-scoped tasks, driving them to completion, and communicating tradeoffs clearly
- Experience working with sensitive data in a regulated environment
- You live within a 75-minute commute of our NYC office (near Union Square) and are able to work in-office 4 days per week
Desired Qualifications
- Previous Experience in Healthcare
- Previous Experience in Airflow & Migrations
- Previous Experience with Kafka Streams
- Experience leveraging AI tools for development
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