Lead Data Engineer

Responsibilities:

• Design, build, and maintain production-grade data pipelines using Airflow and AWS services like Lambda, DynamoDB.
• Own data ingestion from internal systems and third-party integrations (e.g., Google, Bing, external APIs).
• Manage data storage and movement across S3, Snowflake, Snowpipe, and DynamoDB.
• Write and maintain custom Python code that runs reliably in production.
• Work across dev, staging, and production environments with proper deployment and rollback practices.
• Partner with analytics, data science, and product teams to design reliable, usable data models.
• Review code, mentor junior engineers, and help establish best practices for data quality, reliability, and observability.
• Identify and fix performance, cost, or reliability issues in existing pipelines.

Skills:

• Strong experience building and maintaining production data pipelines.
• Deep comfort with Python for data engineering (not just scripting).
• Hands-on experience with Airflow in a real production environment.
• Experience working in AWS, including S3 and managed services.
• Solid SQL skills and experience working with analytical warehouses (Snowflake strongly preferred).
• Experience operating systems across multiple environments (dev / prd).

Benefits:

• 💻 Opportunity to work from home
• 🌟 Excellent work environment
• 🩺 Medical, dental, and vision insurance
• 🌴 Up to 15 days of paid time off
• 🎉 11 company observed holidays
• 👶 8 weeks of paid parental leave
• 💰 401k plan with company match
• 🛡️ Life insurance
• 📈 Professional growth opportunity
• 🌐 Most importantly, an inclusive company culture established by an incredible team!