Collaborate with Data Science, Product Managers and Software Engineers to build robust ETL pipelines that enable the Product Support team to deliver compelling user-facing features
Contribute to architecture decisions, observability tooling, and data quality initiatives that keep our platform robust and maintainable.
Contribute to a scalable internal framework for managing prompt engineering pipelines and other AI workflows.
Enforce and elevate engineering best practices across the AI/ML org, including code quality, testing, and documentation.

5+ years of experience in data engineering, backend engineering, or related roles with a focus on data infrastructure.
Proven experience designing and maintaining scalable data pipelines (e.g., using Airflow, Dagster, or Prefect).
Experience with software development practices like version control, CI/CD, or dbt testing strategies.
Strong proficiency in SQL and Python, with bonus points for Typescript (or similar) experience
Comfortable working with version control, CI/CD systems, and cloud infrastructure (e.g., AWS, GCP, Terraform).
Comfortable navigating ambiguity and working closely with business stakeholders to understand their data needs.
Proven track record of designing high-impact data products and pipelines in fast-paced environments.

Senior Data Engineer

Key skills