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Salary: USD 125,000 - 160,000 / annual
Formlabs is seeking a Senior Data Engineer to build and operate data pipelines that transform raw printer telemetry, manufacturing data, and business system data into trusted, query-ready datasets. The company manufactures professional 3D printers and generates telemetry at enormous scale; the models built on this data drive decisions across product, manufacturing, service, and go-to-market.
You will work primarily in Python and SQL on Google Cloud (Cloud Run and BigQuery), across both real-time and batch data engineering stacks. This is a hands-on role where you own pipelines end-to-end, from ingestion through modeling to the dashboards and services that consume them.
Key responsibilities include:
- Design, develop, and maintain ingestion and transformation pipelines in Python and SQL that handle telemetry at very large scale (datasets measured in trillions of rows) without sacrificing reliability or cost efficiency.
- Contribute to both the Real Time Integrations (RTI) event-driven stack and the BigQuery batch and modeling stack, choosing the right tool for each problem.
- Deploy and operate services on Cloud Run, instrument them with meaningful monitoring and alerting, and respond to production issues.
- Build well-documented, well-tested data models in BigQuery that analysts and stakeholders can use confidently, with clear lineage and sensible definitions.
- Apply partitioning, clustering, incremental processing, and query optimization to keep scale affordable and dashboards fast.
- Partner with analysts, software engineers, and business stakeholders to turn ambiguous questions into durable datasets and pipelines.
- Apply modern software practices—version control, code review, automated testing, CI/CD, and infrastructure-as-code—to data work and help improve how the team builds.
This is a full-time, in-office position based in Somerville, Massachusetts.
REQUIREMENTS:
- 3+ years of professional experience building production data pipelines, with strong, hands-on Python (core of the role, not optional).
- Strong SQL foundation: able 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 that keep large tables performant and affordable.
- Working knowledge of Google Cloud, ideally including Cloud Run, Pub/Sub, Cloud Storage, and IAM—or demonstrated ability to pick up a new cloud quickly.
- Experience with high-volume telemetry, event, IoT, or log data, where dataset size materially changes pipeline design.
- Fluency with Git/GitHub, CI/CD pipelines, and containerized development and deployment.
- Excellent problem-solving, analytical, and communication skills, including ability to explain data caveats to non-technical partners.
- Ability to work in a collaborative, fast-paced environment and learn new technologies quickly.
- Bachelor's degree in Computer Science, Engineering, a quantitative field, or equivalent practical experience.
BONUS:
- Experience with streaming and event-driven architectures (Pub/Sub, Kafka, Dataflow, or similar).
- Experience with dbt or comparable transformation and testing framework.
- Experience instrumenting or consuming device, IoT, or hardware telemetry.
- Familiarity with orchestration tools (Airflow, Dagster, Cloud Composer, or similar).
- Experience with data quality, observability, or lineage tooling.
- Exposure to business systems data (ERP, CRM, eCommerce).
- Experience with Kubernetes or container orchestration.
- Ability to effectively leverage AI coding tools, particularly Claude Code, including building reusable Skills, subagents, or plugins.
