Staff Business Intelligence Engineer - Enterprise & Telemetry Data
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 you'll do
As a Staff Business Intelligence Engineer you will make those diverse data sources trusted, modeled and visualized so every team can move faster and smarter.
- Design and code robust ELT/ETL pipelines in Python and SQL using Airflow or Prefect to integrate data from SAP, Salesforce, MES, PLM, sensor logs and more.
- Develop intuitive dashboards and self-service reports in Sigma, Apache Superset and similar tools; evangelize data-visualization best practices.
- Build and maintain dimensional and star schemas, data marts and semantic layers that serve analytics, reporting and GenAI workloads.
- Optimize query performance and storage costs in Snowflake, Redshift, Trino and related lakehouse architectures (Parquet / Iceberg).
- Collaborate with Finance, Manufacturing, Flight-Test, Supply-Chain and Engineering stakeholders to translate business questions into data models and metrics.
- Implement data quality, lineage and governance (tests, SLAs, documentation, role-based access) to ensure trust and compliance.
- Apply LLM / GenAI techniques—such as metadata enrichment, automated documentation and conversational analytics—to accelerate insight delivery.
- Mentor analysts and engineers; lead design and code reviews; champion a culture of continuous improvement.
What you need:
- 10+ years in Business Intelligence, Data Engineering or Analytics Engineering roles.
- BS or MS in Computer Science, Software Engineering, Data Science or similar.
- Expert-level SQL plus strong Python; solid grasp of software engineering principles.
- Depth in Sigma, Superset or Power BI, from data prep through interactive dashboards.
- Proven success building and orchestrating pipelines with Airflow or Prefect at scale.
- Hands-on experience modeling and querying data in Snowflake, Amazon Redshift, BigQuery or Trino/Presto.
- Familiarity with manufacturing, finance or supply-chain data (SAP, Salesforce, MES, ERP schemas).
- Understanding of time-series / telemetry concepts and how to harmonize them with enterprise data.
- Strong communication skills; comfort translating business requirements into technical designs and vice-versa.
Bonus Requirements
- Experience with dbt, Airbyte, Looker/LookML or semantic-layer tooling.
- Knowledge of streaming frameworks (Kafka, Spark Structured Streaming, Flink).
- Exposure to Kubernetes, Terraform, AWS analytics services (Glue, Lake Formation). Background in aerospace, automotive or other highly regulated industries.