Responsibilities
- Lead the design, implementation, and expansion of the company's data platform, including ingestion pipelines, data warehouse/lakehouse architecture, transformation layers, and data serving infrastructure.
- Define and champion engineering standards, best practices, and architectural patterns for data infrastructure across the organization.
- Collaborate cross-functionally to understand data needs and translate them into scalable, reliable platform capabilities.
- Drive technical decisions on tooling, frameworks, and vendor selection for the data stack (e.g., orchestration, storage, transformation, observability).
- Mentor and level up engineers on the team, providing technical guidance and code review with a focus on quality and long-term maintainability.
- Proactively identify scalability, reliability, and performance bottlenecks and lead efforts to address them.
- Partner with stakeholders across engineering, data science, and business teams to ensure the platform supports current and future analytical and operational needs.
- Contribute to organizational planning and hiring, helping grow the data engineering function.
Requirements
- Extensive experience in data engineering, platform engineering, or a related discipline, with a track record of building and scaling data infrastructure across multiple products or business domains.
- Demonstrated experience designing and implementing end-to-end data platforms, including batch and/or streaming pipelines, data warehouse or lakehouse architectures, and transformation frameworks.
- Deep expertise in at least one major cloud data ecosystem (AWS, GCP, or Azure) and familiarity with modern data stack tooling (e.g., dbt, Spark, Airflow/Dagster, Snowflake/BigQuery/Databricks, Kafka).
- Strong software engineering fundamentals with proficiency in Python and/or Scala/Java for data systems.
- Ability to operate at both the strategic architectural level and the hands-on implementation level.
- Strong communication skills with the ability to influence technical direction and align cross-functional stakeholders.
Nice to Have
- Experience building data platforms in a greenfield or high-growth environment.
- Familiarity with data mesh, data fabric, or federated data architecture patterns.
- Experience with data governance, data cataloging, and metadata management frameworks.
- Prior work in climate tech, sustainability, or a mission-driven organization.
Benefits
- Comprehensive nationwide medical, dental, and vision coverage.
- Flexible vacation policy and ten company-wide holidays, plus annual winter break between Christmas and New Year's
- 16 weeks of fully paid parental and family leave with no tenure requirement
- Remote-friendly work culture with annual company-wide retreats
- Reimbursement for your work-from-home setup and monthly work-from-home stipend
Work Arrangement
Hybrid — Seattle, WA, Oakland, CA
Additional Information
- Benefits vary by country and statutory requirements for international employees.
