Data Engineering Manager

About the role

Kin makes life simpler, more affordable, and better for homeowners - especially in the places where climate risks, rising costs, and outdated systems make it harder. We start with smarter homeowners insurance and expand to everything homeowners need to thrive. Using data, technology, and thoughtful human support, we're building products that are clear, fair, and help homeowners feel confident - so homeowners aren't left behind when they need help most. Founded in 2016, Kin is a remote-first employer with Kinfolk across more than 35 states. We serve customers in 14 states (and counting). Our disciplined growth, strong customer satisfaction, and focus on long-term sustainability fosters outstanding growth, attracts marquee investors, and earns recognition and accolades, including: Built In Chicago's Best Places to Work, Midsize Companies (2021-2026) Forbes' America's Best Startup Employers (2026) Inc. 5000 Fastest-Growing Private Companies Forbes' Fintech 50 (2023-2026) Great Places to Work Certified (May 2024-May 2027) Most importantly, we're building Kin to be a place where people do meaningful work with real impact - for our customers, our communities, and each other. We're excited to tell you more about how you can contribute to our rapid growth, strong unit economics, profitability, and excellent customer ratings. To learn more about how we work and what we're building, visit kin.com and see how we work . We're looking for a Data Engineering Manager to help scale the data platform that powers Kin's analytics, operational decision-making, and machine learning capabilities. This role sits at the center of how data moves through the company-ensuring teams across engineering, product, analytics, and data science can trust and use data reliably at scale. As Kin continues to grow, the complexity and importance of our data ecosystem is growing with it. You'll lead the evolution of our lakehouse architecture, ingestion pipelines, governance tooling, and platform reliability practices while managing and developing a team of data engineers. This is an opportunity to shape the long-term direction of data engineering at a company where data is deeply connected to customer experience, operational efficiency, and business performance. You'll work closely with analytics engineering, data science, application engineering, security, and compliance partners to create scalable systems and operational patterns that make trusted data accessible across the organization.

Responsibilities

• Lead and develop a team of data engineers, driving execution, operational excellence, and long-term growth of the data engineering discipline
• Own the reliability, scalability, and evolution of Kin's data platform infrastructure and lakehouse environment within Databricks
• Design and optimize batch, streaming, and event-driven data pipelines using technologies such as PySpark, Databricks, SQLMesh, Kafka, and Fivetran
• Establish engineering standards for testing, observability, CI/CD, monitoring, incident response, and operational reliability across the data platform
• Define and implement governance, lineage, classification, retention, and access control patterns in partnership with Security, Legal, and Compliance teams
• Drive infrastructure-as-code and GitOps practices for platform resources using tools such as Terraform
• Partner with application engineering teams to build resilient integrations between source systems and the data platform while proactively managing schema and dependency changes
• Collaborate with analytics engineering, product, and data science stakeholders to align platform investments with business priorities and downstream data needs
• Guide the team through large-scale technical initiatives with clear prioritization, iterative delivery, and thoughtful operational tradeoff decisions
• Identify opportunities to improve engineering efficiency and platform scalability through automation, tooling improvements, and thoughtful use of AI-enabled workflows where appropriate
• Success in this role
• By the end of your first year, you should feel confident in your role, trusted as an owner, and proud of the progress you've helped make.
• The data platform is more reliable, scalable, and easier for stakeholders across the business to use confidently
• Data pipelines are observable, well-tested, and consistently meeting freshness, perform

Benefits

Additional Information

Quick Summary Lead the evolution of Kin's modern data platform-owning scalable pipelines, reliable lakehouse infrastructure, and the systems that power analytics, AI, and operational decision-making across the business.

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