Senior Staff Data Engineer

Join Archer, a company at the forefront of urban air mobility. As a Senior Staff Data Engineer, you will play a crucial role in shaping the future of transportation. You will be responsible for designing and evolving our data warehouse and lakehouse architecture, leading data modeling efforts, and driving decisions on storage design and compute optimization. You will work closely with engineering and operations stakeholders and have direct visibility into how your work impacts the company. This is a high-ownership, low-bureaucracy role on a small team.

• Concevoir et faire évoluer l'architecture de notre entrepôt de données et de notre lac de données, y compris les schémas, la structure des couches, les modèles de modélisation et la scalabilité à long terme.
• Diriger les efforts de modélisation des données, y compris la modélisation dimensionnelle, la conception de la couche sémantique et la conception des relations entre entités dans les principaux domaines d'activité.
• Définir les normes concernant la structure, la nomination, la documentation et la gouvernance des données dans l'ensemble de l'architecture Medallion.
• Python proficiency for data transformation and pipeline work
• Experience designing and scaling data warehouses or lakehouses in cloud environments (Snowflake, Databricks, BigQuery, or equivalent)
• Advanced SQL — complex joins, aggregations, window functions, query optimization, and schema design
• Experience with data governance concepts — lineage, cataloging, access control, quality frameworks
• Strong grasp of dimensional modeling, Medallion / Lakehouse architecture, and semantic layer concepts
• 7+ years of data engineering experience with demonstrated depth in data modeling and warehouse design
• Familiarity with orchestration tools (Airflow, Prefect, or equivalent)
• 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 communicate well with non-technical partners and translate ambiguity into concrete data designs
• 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're comfortable operating on a small, high-trust team without a lot of process overhead