Data Engineer
Build and scale data architecture, governance, and ETL pipelines across Snowflake, Databricks, and cloud platforms. The role requires 3+ years of data engineering experience, strong API and pipeline expertise, and the ability to collaborate across technical and business teams.
About the job
Responsibilities
- Architect and manage production data pipelines in Snowflake and their consumption in Sigma.
- Build and optimize ETL pipelines for internal and external demo use cases.
- Scale demo asset data across cloud data warehouses.
- Partner with infrastructure engineering to ensure high availability of key data assets.
- Build and scale data governance policies using scalable, repeatable processes.
- Collaborate cross-functionally with Product, Engineering, and GTM teams.
Requirements
- 3+ years of relevant data engineering experience.
- Strong experience working with APIs and building pipelines from various systems into cloud data platforms such as Snowflake and Databricks.
- Experience deploying data governance frameworks.
- Strong communication and collaboration skills.
- Ability to work effectively in ambiguous, fast-moving environments.
- Startup experience.
Nice-to-Haves
- Familiarity with dbt.
- Advanced Python knowledge.
- Advanced knowledge of data orchestrators such as Astronomer, Airflow, or Dagster.
- Advanced experience with public clouds such as AWS or Google Cloud.
- Interest in continuously learning about and sharing knowledge of the evolving data ecosystem.
Compensation and Benefits
- Base salary: $140,000–$180,000 annually.
- Stock options and comprehensive benefits package.
- Equity.
- Health benefits.
- Flexible time off.
- Paid bonding time for new parents.
- Traditional and Roth 401(k).
- Commuter and FSA benefits.
- Lunch program.
- Dog-friendly office.
Skills
Snowflake, Databricks, ETL, Fivetran, dbt, Sigma, Hightouch, Metaplane, Python, Airflow, Dagster, AWS, GCP, Data Governance
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