What You’ll Work On
- Building robust pipelines to ingest, transform, and consolidate data from diverse sources (e.g., MongoDB, Airtable, PostHog, production databases).
- Designing dbt models and transformations to standardize and unify many disparate tables into clean, production-ready schemas.
- Implementing scalable, fault-tolerant data workflows with Fivetran, dbt, SQL, and Python.
- Partnering with engineers, data scientists, and business stakeholders to ensure data availability, accuracy, and usability.
- Owning data quality and reliability across the stack, from ingestion through to consumption.
- Continuously improving pipeline performance, monitoring, and scalability.
What We’re Looking For
- Proven experience in data engineering, with strong knowledge of SQL, Python, and modern data stack tools (Fivetran, dbt, Snowflake or similar).
- Experience building and maintaining large-scale ETL/ELT pipelines across heterogeneous sources (databases, analytics platforms, SaaS tools).
- Strong understanding of data modeling, schema design, and transformation best practices.
- Familiarity with data governance, monitoring, and quality assurance.
- Comfort working cross-functionally with engineering, product, and operations teams.
Bonus: prior experience supporting machine learning workflows or analytics platforms.
Benefits
- Generous equity grant vested over 4 years
- A $10K housing bonus (if you live within 0.5 miles of our office)
- A $1K monthly stipend for meals
- Free Equinox membership
- Health insurance