Sr. Staff Data Engineer

About the Role

Archer is building the future of urban air mobility, and our data platform is what makes intelligent decisions possible — from manufacturing operations to flight analytics. We're looking for a Senior Staff Data Engineer who brings deep expertise in data modeling and warehouse design: someone who can architect scalable, well-structured data systems and set the technical direction for how data is organized, governed, and consumed across the company. This is a high-ownership, low-bureaucracy role on a small team. You'll shape how data is modeled and stored, work closely with engineering and operations stakeholders, and have direct visibility into how your work shapes the company.

Responsibilities

• 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

Requirements

• 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

Nice to Have

• 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

How You Work

• 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

Pay

For this position we are targeting a base pay between $207,400 - $259,200. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.