Senior Data Engineer

Role Overview

You’ll be joining a small, high-impact data engineering team within Federato’s AI/ML organization. Our focus is on building the infrastructure and internal frameworks that empower machine learning engineers to develop, deploy, and iterate on AI-powered features ranging from prompt-based LLM workflows to more traditional model-driven systems. We collaborate closely with ML, analytics, and product teams to ensure data and tooling are reliable, scalable, and aligned with the needs of our AI-native platform.

What You'll Be Doing

• 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.

Who We Hope You Are

• 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
• Comfort 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.

Bonus Points for

• Prior experience working in or adjacent to insurance, fintech, or risk modeling domains.
• Prior exposure to ML ops or experience supporting AI/ML-driven products
• Enthusiasm for building internal tools or frameworks to improve team velocity.
• Contributions to open-source data tools or involvement in the data community.

Compensation

$160,000 - $210,000 a year

Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks.