Lead Data Engineer

About the Role

We’re hiring a Data Engineer to help own and scale our core data platform. This role is hands‑on and production‑focused: you’ll design, build, and maintain data pipelines that power analytics, machine learning, and operational systems.

We’re especially interested in candidates who combine strong data engineering fundamentals with either analytics depth or Dev Ops / platform experience
.

Design, build, and maintain production‑grade data pipelines using Airflow and AWS services like Lambda and Dynamo

DB.

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.

• Core Requirements
• 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).
• Ability to mentor others through code review, design discussions, and troubleshooting.
• Bonus Skills
• Experience with Kubernetes or containerized workloads.
• Dev Ops or platform experience (CI/CD, infrastructure‑as‑code, monitoring).
• Analytics experience (data modeling, working directly with analysts or stakeholders).
• Experience integrating with external APIs and managing schema or contract changes.
• History of improving data reliability, latency, or cost at scale.
• Experience as a technical mentor—reviewing code, setting standards, and helping the team make better engineering decisions.
• Can explain why a system is built a certain way, not just how.

• Opportunity to work from home
• Excellent work environment
• Medical, dental, and vision insurance
• Up to 15 days of paid time off
• 12 company observed holidays
• 401k plan with company match
• Life insurance
• Professional growth opportunity
• Most importantly, an inclusive company culture established by an incredible team!