Engineering Manager, Data Engineering

Kin is on a mission to change home insurance from what it is to what it should be. Whether we’re leveraging data to create customizable coverage or providing claims service that goes above and beyond expectations, our members are at the heart of everything we do. In the face of ever-growing climate risk, they deserve an insurance company that cares about them. We aim to stick with our members through thick and thin.

Use efficient technology that lets homeowners buy directly from us to keep costs down: This is the essence of Kin. Our approach has fostered amazing growth, attracted marquee investors, and earned us accolades, including being named to:

• Built In Chicago's Best Places to Work, Midsize Companies (2021-2024).

• Forbes' America's Best Startup Employers (2021- 2023).

• Inc. 5000 Fastest-Growing Private Companies.

• Forbes’ Fintech 50.

Simply put, our people are what make us great – we need forward-thinking, inspired game-changers like you to join us in our mission.

So, what’s the role?

We are looking for a passionate engineering manager to lead our Data Engineering team. You should be comfortable working with geographically distributed teams and understand the nuances of being a team player. In this role, you will be responsible for leading a team of about five data engineers to deliver data solutions, while relentlessly improving performance, scalability, and maintainability. Your team will work upstream from Business Intelligence, Data Science, and Data Science Engineering. This role has no functional peer at the organization; you and your team are the face of data at Kin.

A day in the life could include: 

• Lead and manage the Data Engineering team at Kin, owning data ingestion, data storage, data pipeline management, data mastering, and data governance/compliance

• Maintain high-trust relationships with Engineering, Product, and internal business partners

• Outline and execute on a Data Engineering strategy, balancing immediate business objectives with long-term engineering goals

• Guide the team when iteratively navigating through large engineering initiatives

• Promote a culture that values ownership of outcomes

I’ve got the skills… but do I have the necessary ones?

• Experience leading and managing a data engineering team in a startup environment

• Proven track record of modern engineering practices including CI/CD, automated testing, and iterative development

• Expertise in data stacks like Snowflake and Databricks

• Knowledge of data pipeline tools like DBT, Airflow, DMS, and Airbyte

• Knowledge of data stream tools like Kafka or Flink

• Hands-on experience in large-scale and complex data solutions development projects (we generally use Python for data engineering)

• Experience with enterprise data modeling

Bonus Points:

• Exposure to AI/ML and predictive analytics

• Experience with infrastructure as code solutions like Terraform

Oh, and don’t worry, we’ve got you covered! 

• Medical, Dental, Vision, Disability and Life Insurance

• Flexible PTO policy 

• Remote work

• Generous equity package

• 401K with company match

• Parental leave

• Continuing education and professional development

• The excitement of joining a high-growth Insurtech company and seeing your work make an impact

Kin is the only pure-play, direct-to-consumer digital insurer focused on the growing home insurance market. We make policies convenient and affordable through a technology platform that delivers a seamless user experience, customized options for coverage, and fast, high-quality claims service. Kin is a fully licensed carrier that offers coverage through its reciprocal exchanges which are owned by its policyholders. To learn more, visit www.kin.com.

Kin is proud to be an Equal Employment Opportunity and Affirmative Action Employer. We don't just accept difference – we honor it, nurture it, and celebrate it. We don’t discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.