Build and scale production data systems spanning laboratory, manufacturing, battery, and business data. Responsibilities include developing ELT pipelines, architecting secure AWS data movement, modeling warehouse data, optimizing SQL, managing infrastructure as code, implementing monitoring and data quality controls, and partnering with scientists and engineers. The role requires strong Python, SQL, cloud, software engineering, and end-to-end ownership skills.
We’re hiring a Data Engineer to help build and scale our data backbone. This will be a high impact position on the Anthro Data Team, with significant ownership across pipelines, modeling, and cloud infrastructure.
Our data spans lab characterization equipment, high-volume manufacturing systems, thousands of battery cycler channels, and business software. Your day to day will include:
- Design and build production-grade ELT pipelines for lab and manufacturing data
- Architect secure, reliable data movement between on-prem systems and AWS
- Develop well-structured, performant warehouse data models for analytics and ML
- Write, test, and optimize complex SQL used in production dashboards and workflows
- Deploy and manage AWS infrastructure using infrastructure-as-code
- Implement monitoring, data quality checks, and system observability
- Partner closely with scientists and engineers to translate real-world workflows into reliable data systems
Requirements
- Bachelor’s degree in CS, Engineering, Mathematics, or a scientific discipline
- 3-5+ years of data engineering experience
- Strong Python — able to write clean, modular, well-tested, production-ready code
- Advanced SQL — comfortable designing schemas, reading query plans, and tuning performance at scale
- Experience with data modeling and query optimization in a cloud data warehouse
- Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform, CDK, CloudFormation)
- Strong software engineering fundamentals (version control/Git, testing, CI/CD)
- Ability to operate independently and own data systems end-to-end
Nice to Have:
- Experience with manufacturing or industrial data
- Scientific background or familiarity with lab-based research
- AWS and/or ClickHouse-specific experience
- Experience supporting AI/ML data pipelines
Benefits
- Competitive salary and equity compensation commensurate with experience. Expected salary range for posted level is $120-160k
- 15 Vacation Days, 10+ Holidays, Sick time off
- Full medical, dental, and vision coverage for team members, 60% coverage for dependents
- 401k with match
- Paid parental leave with flexible return-to-work policy
- Diverse and inclusive work environment
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