Senior Data Engineer & Scientist
About The Position
As a Senior Data Scientist focused on data engineering, this role discovers, connects, transforms, and operationalizes engineering data and knowledge so it can be reliably used by downstream AI systems, applications, and engineering workflows. The position works across distributed data sources, structured and unstructured content, metadata, lineage, data quality, cloud data services, and reusable headless data capabilities. It helps make engineering data discoverable, trustworthy, and ready for retrieval and agent use. The role is onsite with colleagues Monday through Thursday. On Fridays, employees may choose their work location based on what their work requires. The position supports production data services and delivers measurable value across multiple engineering use cases.
Requirements
- Bachelor’s degree in data engineering, computer science, engineering, or a related field.
- Two to five years of relevant experience is acceptable.
- Experience discovering and integrating distributed data sources.
- Experience with structured and unstructured engineering data.
- Experience with metadata, cataloging, lineage, and discoverability.
- Experience with data quality, validation, and observability.
- GCP or comparable cloud data-platform experience.
- Experience preparing data and knowledge for retrieval and agent use.
- Experience with graph, entity, and relationship modeling.
- Experience building reusable headless data services.
- Experience with GitHub workflows, CI/CD, and automated testing.
- Experience with requirements, specifications, constitutions, contracts, and AI harnesses.
- Experience with security, access control, privacy, and governance.
- Production deployment and operational-support experience.
Nice To Haves
- Master’s degree preferred.
Responsibilities
- Discover engineering data and knowledge sources across distributed systems and repositories.
- Build data-ingestion and integration pipelines.
- Connect structured and unstructured engineering data.
- Implement metadata, cataloging, lineage, and discoverability capabilities.
- Establish data quality, validation, and observability practices.
- Implement GCP or comparable cloud data platform services.
- Design interfaces for downstream AI systems and applications.
- Prepare data and knowledge for retrieval and agent use.
- Support graphs, entities, and relationship modeling.
- Build reusable headless data services.
- Use GitHub workflows, CI/CD, Terraform, and automated testing.
- Prepare requirements, specifications, constitutions, contracts, context, and AI harnesses.
- Implement security, access control, privacy, and governance controls.
- Deploy and support production data services.
- Use Terraform for infrastructure provisioning and repeatable environment management.
- Discover and connect priority engineering data and knowledge sources.
- Deliver reliable ingestion, integration, transformation, and validation pipelines.
- Improve metadata, lineage, discoverability, and operational observability.
- Establish repeatable Terraform, GitHub, testing, and deployment practices.
Benefits
- Health insurance and holistic wellness programs, including incentives.
- Fertility coverage and adoption/surrogacy assistance.
- Up to 15 vacation days, paid holidays, sick leave, and options supporting volunteer and parental leave.
- 401(k) matching.
- Educational and training opportunities through company programs.
- Tuition assistance and student debt support.
- Incentive eligible.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
