Responsibilities
- Design, build and maintain scalable data pipelines and models using SQL, dbt, and cloud warehouses, owning the entire data engineering function.
- Implement and optimize ETL/ELT workflows to transform raw data into high-quality datasets while reducing latency and costs.
- Develop semantic layers and data catalogs that enable self-service analytics and flexible dashboarding for business users.
- Collaborate with cross-functional teams to define requirements, data contracts, and translate business goals into scalable solutions.
- Balance urgent needs with long-term infrastructure goals while diagnosing and resolving production issues at scale.
Requirements
- 5+ years in data engineering with experience building data infrastructure from early stages and making architectural decisions.
- Strong judgment and autonomy - comfortable with ambiguity, can prioritize effectively, explain trade-offs to executives, and balance speed with quality.
- Strong hands-on experience with ETL/ELT pipelines, data warehousing (Snowflake preferred), orchestration tools (Airflow), and dbt.
- Advanced SQL skills for complex queries on large datasets, with understanding of performance and cost trade-offs.
- Experience with data quality, governance, and leading technical discussions across teams of varying expertise.
Nice to Have
- Proficiency with GitHub, Python, and data visualization tools;
- bonus points for ML feature engineering or AI agents experience.
Benefits
- Competitive Salary: Make some $$$.
- Very Competitive Benefits: Fully paid Health, Vision, and Dental insurance.
- 4-day work week.
- Unlimited PTO.
- Fully Remote Office & Culture: Our team is spread across the US day to day, but we travel for department & company off-sites and retreats.
- Free Product: Free cat food every month.
Additional Information
- Our team is spread across the US day to day, but we travel for department & company off-sites and retreats.
