Sr. Staff Data Engineer
- Own the design and evolution of our data warehouse and lakehouse architecture — schemas, layer structure, modeling patterns, and long-term scalability
- Lead data modeling efforts: dimensional modeling, semantic layer design, and entity relationship design across key business domains
- Define standards for how data is structured, named, documented, and governed across the Medallion Architecture (bronze → silver → gold)
- Partner with analytics engineers and business stakeholders to translate domain requirements into robust, reusable data models
- Drive decisions on storage design, partitioning strategies, and compute optimization for query performance and cost efficiency
- Contribute to data governance — lineage, cataloging, access control, and quality frameworks
- Build and maintain production-grade pipelines where needed, with a focus on reliability and idempotency
- Participate in architecture reviews and bring Senior Staff-level judgment to data stack decisions
- 7+ years of data engineering experience with demonstrated depth in data modeling and warehouse design
- Strong grasp of dimensional modeling, Medallion / Lakehouse architecture, and semantic layer concepts
- Advanced SQL — complex joins, aggregations, window functions, query optimization, and schema design
- Experience designing and scaling data warehouses or lakehouses in cloud environments (Snowflake, Databricks, BigQuery, or equivalent)
- Python proficiency for data transformation and pipeline work
- Familiarity with orchestration tools (Airflow, Prefect, or equivalent)
- Experience with data governance concepts — lineage, cataloging, access control, quality frameworks
- Experience with dbt or similar transformation/modeling frameworks
- Exposure to agentic or AI-assisted data infrastructure
- Experience in a fast-moving startup or aerospace/manufacturing environment
- You take ownership — if something is broken or unclear, you fix or clarify it
- You think in systems: you model data to be reusable, not just functional
- You communicate well with non-technical partners and translate ambiguity into concrete data designs
- You're comfortable operating on a small, high-trust team without a lot of process overhead
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