The role
What you'll do
- 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.
- 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
The bar
What you'll bring
- 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
Additional notes
Other
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
What We're Looking For
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
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
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. 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.