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Salary: USD 80,000 - 125,000 / annual
Formlabs is seeking a Data Engineer to join the Systems department in Somerville, MA. You will build and operate data pipelines that transform raw printer telemetry, manufacturing data, and business system data into trusted, query-ready datasets at enormous scale. The role is hands-on and full-time, requiring ownership of pipelines end-to-end from ingestion through modeling to consumption by dashboards and services.
Key responsibilities include:
- Designing, developing, and maintaining ingestion and transformation pipelines in Python and SQL that handle telemetry at very large scale (trillions of rows) while maintaining reliability and cost efficiency
- Contributing to both Real Time Integrations (RTI) event-driven stack and BigQuery batch/modeling stack, selecting the appropriate tool for each problem
- Deploying and operating services on Cloud Run with meaningful monitoring, alerting, and incident response
- Building well-documented, well-tested data models in BigQuery with clear lineage and sensible definitions
- Optimizing for cost and performance through partitioning, clustering, incremental processing, and query optimization
- Partnering with analysts, software engineers, and business stakeholders to convert ambiguous questions into durable datasets and pipelines
- Applying modern software practices (version control, code review, automated testing, CI/CD, infrastructure-as-code) to data work
Requirements:
- 3+ years of professional experience building production data pipelines with strong, hands-on Python (core requirement, not optional)
- Strong SQL foundation: ability to write, debug, and optimize complex SQL from scratch; comfortable with query plans, joins, window functions, and aggregation at scale
- Experience with BigQuery or comparable columnar warehouse (Snowflake, Redshift, Databricks), including design decisions for large-table performance and cost
- Working knowledge of Google Cloud, ideally Cloud Run, Pub/Sub, Cloud Storage, and IAM; or demonstrated ability to learn new cloud platforms quickly
- Experience with high-volume telemetry, event, IoT, or log data where dataset size materially affects pipeline design
- Fluency with Git/GitHub, CI/CD pipelines, and containerized development/deployment
- Excellent problem-solving, analytical, and communication skills, including ability to explain data caveats to non-technical partners
- Ability to work in collaborative, fast-paced environment and learn new technologies quickly
- Bachelor's degree in Computer Science, Engineering, quantitative field, or equivalent practical experience
Bonus qualifications: streaming/event-driven architectures (Pub/Sub, Kafka, Dataflow), dbt or transformation frameworks, device/IoT/hardware telemetry experience, orchestration tools (Airflow, Dagster, Cloud Composer), data quality/observability/lineage tooling, business systems data (ERP, CRM, eCommerce), Kubernetes or container orchestration, AI coding tools (Claude Code with Skills/subagents/plugins).
