Related skills
terraform sql python typescript dbt📋 Description
- 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.
🎯 Requirements
- 5+ years in data/backend engineering focusing on data infra.
- Designing scalable data pipelines with Airflow, Dagster, or Prefect.
- Experience with version control, CI/CD, and dbt testing strategies.
- Proficient in SQL and Python; TypeScript bonus.
- Comfortable with cloud infrastructure (AWS, GCP) and Terraform.
- Proven track record delivering data products/pipelines in fast-paced environments.
🎁 Benefits
- Stock options, benefits and additional perks.
- Experience in insurance, fintech, or risk modeling.
- ML ops exposure or AI/ML-driven product support.
- Enthusiasm for building internal tools to boost velocity.
- Contributions to open-source data tools or data community.
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