Sr. Manager, Data Engineering

Federato is on a mission to defend the right to efficient, equitable insurance for all. We enable insurers to provide affordable coverage to people and organizations facing the issues of today - the climate crisis, cyber‑attacks, social inflation, etc. Our vision is understood and well funded by those behind Salesforce, Veeva, Zoom, Box, etc.

Federato is the only AI‑native platform that spans the full policy lifecycle and changes the way insurance work gets done. Better decisioning is built‑in, not bolted on: insurers’ unique portfolio goals, strategies, rules, and appetite are part of the workflow so underwriters win the right deals, faster. From the moment a submission hits an underwriter’s inbox, AI is put to work, triaging submissions with a focus on high‑appetite business, delivering real‑time feedback on the portfolio, and consolidating workflows into a single proven system.

Federato drives better business outcomes.

Our Data Science Organization Drives Insights, Models, And Engineering Solutions That Power Our Products And Customer Implementations. We Operate Across Three Core Functions

• Analytics – turning data into business insights
• Core Engineering – building robust data and ML infrastructure (Data Engineering + ML Engineering foundations)
• Modeling – developing, deploying, and maintaining advanced ML models and forward‑deployed solutions

We collaborate closely with Product, Product Engineering, Forward Deploy Engineering, and Customer Success to design, build, and operationalize data products that deliver measurable impact.

We’re looking for a Sr. Manager, Data Engineering to lead execution across the Data Engineering organization, ensuring our vision translates into consistent, high‑quality delivery.

This role combines people leadership, agile delivery management, and cross‑functional coordination. You’ll lead a team of 6–9 Data Engineers and Data Analytics Engineers, starting with an existing group of 4–5 and growing the team. You’ll define and refine our delivery processes while acting as a key connection between Data Science, Product, Engineering, and Customer Success.

You’ll partner closely with the Sr. Director of Data Science (vision & strategy) and data leaders (Analytics, Core Engineering, and Modeling) to ensure the team executes efficiently and effectively.

• Manage a team of Data Engineers and Data Analytics Engineers owning our data infrastructure, including our medallion layers, data pipelines, and collaborating closely with MLEs on LLM Operations and agentic products.
• Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross‑functional teams.
• Partner with function leads and senior leadership to align growth paths, performance expectations, and strategic goals with technical excellence standards.
• Translate the Data Engineering vision into clear objectives, priorities, and milestones, ensuring effective project scoping, resourcing, and delivery.
• Define and refine agile workflows tailored to data engineering, managing key rituals such as design sessions, sprint planning, and retrospectives.
• Serve as the primary delivery interface across Product, Engineering, and Customer Success, ensuring alignment, transparent communication, and continuous improvement of team operations.
• Drive hiring excellence by attracting, developing, and scaling a high‑performing team aligned with business needs.

• 8+ years of experience in data science, data engineering, or machine learning–related roles.
• 4+ years in a people management or delivery management role (directly leading technical contributors).
• Proven experience managing cross‑functional ML technical teams and driving delivery across multiple work streams.
• Strong understanding of data science lifecycle (from ideation and experimentation to deployment and maintenance).
• Practical experience with agile methodologies (Scrum, Kanban) and delivery facilitation.
• Excellent communication, organizational, and stakeholder management skills.
• Ability to balance technical depth with delivery discipline, ensuring outcomes, not just output.
• Experience with LLM Ops, agentic…