Data Engineer

Requirements:

• 4 - 6 years owning production data pipelines independently.
• Python and SQL - strong fundamentals, not just usage.
• Hands-on with a cloud data warehouse (BigQuery preferred) and DBT.
• AWS ecosystem familiarity - S3 or equivalent.
• Apache Airflow or equivalent orchestration in production.
• Startup or small team experience - comfortable as the sole DE.

Good to have:

• PySpark or distributed compute.
• Real-time data handling - Kafka or equivalent.
• ML feature store experience.
• Event tracking pipeline experience.

You're a Fit If:

• You prefer owning systems end-to-end over working on isolated tickets.
• You are comfortable with minimal structure and no existing playbook.
• You make pragmatic decisions - not over-engineering early, but not creating long-term debt blindly.
• You can prioritize ruthlessly between business needs and technical correctness.
• You care about clarity and usability of data, not just pipeline completion.
• You can work directly with stakeholders without needing intermediaries.
• You've worked in a startup before or actively want that environment.
  • You can mentor and bring up junior engineers without it becoming a management distraction.