Senior Data Engineer

About this role

QUICK SUMMARY

Build Kin’s next-generation lakehouse architecture, design scalable pipelines, and ensure trusted, secure data for enterprise reporting in a fast-growing insurtech.

WHO WE ARE

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simpler, more affordable, and better for homeowners — especially in the places where climate risks, rising costs, and outdated systems make it harder.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 13 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 (2021-2024)

- Inc. 5000 Fastest-Growing Private Companies

- Forbes’ Fintech 50 (2025-2026)

- Great Places to Work Certified (2024-2026)

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 http://kin.com and see how we work https://www.linkedin.com/company/kin-insurance/life/kin/.

THE OPPORTUNITY

We're looking for a Senior Data Engineer to turn raw, complex data into trusted, well-modeled datasets that power reporting and decision-making across Kin. As we grow, the accuracy and structure of the data underneath our reporting matters more every quarter — teams can only move as fast as the data they're standing on.

You'll own the modeling layer between raw source data and the people who depend on it: analytics engineers, BI, and business stakeholders across Finance, Marketing, and Product. You'll work closely with App Engineering to understand source systems and with downstream teams to make sure what you build actually answers their questions.

YOUR RESPONSIBILITIES

- Design and build scalable, production-grade data pipelines and data models to power downstream analytics and enterprise reporting

- Implement and enforce data validation, testing, and QA standards across data models to ensure accuracy and reliability

- Partner with App Engineering to understand source systems and define how raw data should be captured and modeled downstream

- Collaborate with Analytics Engineering, BI, and business stakeholders to translate ambiguous reporting needs into scalable, well-modeled datasets

- Ensure data models comply with data security and privacy regulations (e.g., GDPR, CCPA, GLBA) through access controls and monitoring

- Mentor other data engineers on modeling best practices, documentation, and data processing patterns

- Leverage AI-assisted development tools where appropriate to improve engineering efficiency, code quality, and observability

SUCCESS IN THIS ROLE

In your first 6–12 months at Kin, success is less about checking boxes and more about the impact you create. You’ll use your skills and judgment to take ownership of meaningful work, improve how we operate, and help move Kin’s mission forward. Along the way, you’ll deliver outcomes that make a real difference for both Kinfolk and the homeowners we serve.

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.

- Well-modeled, production-ready datasets are the default source of truth for reporting, cutting down on one-off requests and rework

- Data validation and QA standards are consistently applied, resulting in measurable improvements in data quality and stakeholder trust

- Cross-functional partners rely on your models to make faster, better-informed decisions

WHAT YOU’LL BRING

- 4+ years of experience in data engineering, analytics engineering, or dimensional modeling roles, building production data models

- Advanced SQL skills, with experience transforming data from multiple sources into a scalable warehouse or lakehouse

- Proficiency in Python (Pandas, NumPy, etc.) for data transformation and pipeline development

- Expertise in dimensional modeling, ELT workflows, and modern data architecture patterns

- Proven ability to model raw, complex data into well-structured, analytics-ready datasets

- Experience working with platforms such as Databricks, Snowflake, or Redshift

- Ability to translate ambiguous business requirements into scalable, well-modeled datasets

- Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders

HOW WE HIRE

We believe a great hiring experience should be clear, respectful, and human. We’ll accept applications for this position until October 9th, 2026. While our recruiting team uses AI tools for efficiency, resumes are still screened by Kin’s in-house recruiters, and candidate evaluations and hiring decisions are made by recruiters and hiring teams. Rest assured, real people make real decisions.

The hiring process and timeline for each role will vary, depending on the position. However, here are some things you can expect from us:

- Prompt updates and feedback following interviews

- Interviews with recruiters, hiring managers, and members of teams

- Skills assessment relevant to the position, if applicable

- Genuine, thoughtful human interaction at every step

HOW WE SUPPORT YOU

We offer a comprehensive, competitive benefits program, allowing you to choose the benefits…