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Staff Data Engineer - Insurance Data

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.

We 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?

Currently our data engineering organization is building data lakehouses in Databricks that will be used for enterprise reporting. Data Engineering teams are split into two general focus areas–growth data and insurance data.

As a Staff Data Engineer, you will be the technical lead within a team of data engineers focused on insurance data related to claims, policies, products, rates, pricing, renewals, risk, and more.

You will be responsible for designing and developing data pipelines and modeling raw data for downstream ingestion. You’ll play a pivotal role in ensuring the quality, integrity, and security of our data assets.  You’ll also be responsible for mentoring and guiding data engineers on your team and across the organization, while collaborating with other engineers, product managers, analysts, and stakeholders. 

You will also lead a cross-functional project team with members from AppEng, DataEng, BI, and business stakeholders. This team is tasked with designing solutions to produce effective reporting, implementing data validation standards, and QA procedures to ensure effective data lifecycle and management practices.

Are we a fit for one another?

We recognize that not everyone will be a fit for us, and we’re not a fit for every data engineering professional. Here are some things to help you decide:

  • You have a depth of experience in modern big data environments. More than just cloud-based data experience, you’ve worked in a lakehouse environment and built end to end data solutions with modern tools. At this level, advanced knowledge and experience with SQL and Python is expected. The same goes for database design. The thing that will really impress us is your ability to set up jobs and notebooks and teach other engineers how to use these more advanced tools.

  • You have insurance domain knowledge. You’re not just following Jira stories and mapping data to existing models; you’re designing the models and writing the schemas, often with some ambiguous specs. Your problem solving skills and insurance knowledge will be essential to setting your team and downstream stakeholders up for success. 

  • You like connecting your technical work to business goals and teams. You establish relationships and trust with stakeholders to better define technical requirements, and ensure your team’s work aligns with business goals.

  • You prioritize data quality and integrity to optimize performance. Assessing the effectiveness and accuracy of data sources and data gathering techniques, analyzing database configurations, and evangelizing iterative testing practices is second nature.

  • You value documentation. Maintaining a centralized metadata catalog documenting data assets, schemas and lineage is a standard practice for you.

  • You want to work for a company that prioritizes security and compliance. We operate in a highly regulated industry, so we have high standards for data security. You’re someone who will ensure that pipelines and storage solutions comply with Kin’s standards on privacy regulations such as GDPR, CCPA, and GLBA, as well as monitor access logs and audit trails to detect unauthorized data access or usage.

You probably shouldn’t apply if:

  • You prefer to have clearly defined requirements and previously established solutions to iterate or build upon. 

  • You only want to do the most exciting or strategic work. Our teams are collaborative, and we believe in running through walls together. The work is hard and everyone contributes to hands-on problem solving, including leads.

  • You haven’t led or don’t want to lead teams and projects. While you won’t have direct reports, you will be a pivotal leader within our data org, and that comes with great responsibility.

  • You want to spend most of your time doing heads-down coding OR you only want to manage projects and do code reviews. You’ll be in a lot of meetings, you’ll be coaching and mentoring teams. You will have to communicate a ton in your position, and you’ll have to optimize your heads-down time for production. This position requires excellent communication and time management skills. So if you’re lacking either, this might not be for you.

  • Your technical skills aren’t what they used to be. We get it, as you grow professionally and focus more on architecture and leadership, hands-on coding skills wane. Here at Kin, we expect you to be able to write good code as well as design great schemas. 

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

We offer a comprehensive benefits program, allowing you to choose the benefits that are best for you and your family including: Medical, Dental, Vision, Life Insurance and Disability Insurance options, Employee Assistance Program, as well as elective voluntary benefits such as accident insurance, hospital indemnity, critical illness, legal assistance and pet insurance.  

In addition to these benefits, we also are excited to offer the following: 

  • Competitive salary and equity  

  • 401K with company match of up to 4%  

  • Flexible PTO for exempt employees, along with 8 company-observed holidays 

  • A paid parental leave program that provides 100% salary continuation of up to 14 weeks for birthing parents and 8 weeks for non birthing parents 

  • Continuing education and professional development opportunities

For Sales Agents and Customer Service Agents: These roles sit in any of the following 30 states: AL, AZ, CO, FL, ID, IL, IN, KS, KY, MA, MD, ME, MI, MN, MO, MT, NC, NE, NM, NV, NY, OH, OK, PA, SC, TN, TX, UT, VT, VA, WA, and WI.

For all other positions, these roles can sit in any of the following 40 states: AL, AR, AZ, CA (exempt only), CO, CT, FL, GA, ID, IL, IN, IA, KS, KY, MA, ME, MD, MI, MN, MO, MT, NC, NE, NJ, NM, NV, NY, OH, OK, OR, PA, SC, SD, TN, TX, UT, VT, VA, WA, and WI. Please only apply if you are able to live and work full-time in one of the states listed above.

State locations and specifics are subject to change as our hiring requirements shift.

About Kin

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.

 

EEOC Statement

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.

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What You Should Know About Staff Data Engineer - Insurance Data, Kin Insurance

At Kin, we’re on a mission to transform home insurance into something that truly meets the needs of homeowners. As a Staff Data Engineer focusing on Insurance Data, you'll play a pivotal role in our journey. We’re leveraging innovative technology to enhance customer experience and provide customizable coverage while ensuring claims are handled effectively. Your expertise will bring our data lakehouse initiatives to life using Databricks, as you’ll lead a talented team of data engineers within our insurance data sector. This includes crafting robust data pipelines, modeling data to improve reporting, and maintaining the integrity and security of our data assets. You’ll mentor junior engineers, guide best practices across teams, and lead projects that span various functions, ensuring our reporting solutions are world-class and data management is top-notch. We’re looking for someone with deep experience in modern big data environments and knowledge of the insurance domain, who can design data models intuitively and create documentation that supports our operations. If you thrive on collaboration and enjoy connecting your technical expertise to business outcomes, we want to hear from you. With us, you’ll be part of a rapidly growing company that values innovation and integrity, all while enjoying great benefits like flexible PTO, career development, and competitive salaries. If you’re ready to make a difference in the insurance industry through data engineering, join us at Kin and help us change the narrative of home insurance.

Frequently Asked Questions (FAQs) for Staff Data Engineer - Insurance Data Role at Kin Insurance
What responsibilities does a Staff Data Engineer at Kin have?

As a Staff Data Engineer at Kin, you will lead a team focused on insurance data, playing a crucial role in designing data pipelines and modeling raw data. You’ll ensure the quality and integrity of data assets while mentoring junior engineers. Your responsibilities will include collaborating with cross-functional teams and stakeholders to implement effective reporting solutions and adhering to high standards of data security and compliance.

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What qualifications are needed for the Staff Data Engineer position at Kin?

Candidates for the Staff Data Engineer role at Kin should have a strong background in big data environments and experience with Databricks and SQL. Proficiency in Python for data solutions is essential, alongside a solid understanding of the insurance industry and related data practices. Experience in documenting data assets and a commitment to data quality and integrity will also be crucial.

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How does the Staff Data Engineer role at Kin connect to business goals?

In the Staff Data Engineer position at Kin, you'll be expected to align your technical work with business objectives by building strong relationships with stakeholders. This involves clearly defining technical requirements, ensuring that your team's data strategies effectively support business operations and contribute to the overall mission of improving home insurance.

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What can a Staff Data Engineer expect from Kin's company culture?

Kin fosters a collaborative and innovative company culture where every team member is encouraged to contribute ideas and solutions. As a Staff Data Engineer, you’ll engage in hands-on problem-solving alongside your peers and take on leadership responsibilities that impact the growth and success of the organization. Kin celebrates diversity and is dedicated to providing a supportive work environment.

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What are the key challenges faced by a Staff Data Engineer at Kin?

A Staff Data Engineer at Kin faces the challenge of working with ambiguous specifications while designing data models tailored to the insurance domain. Additionally, managing cross-functional projects and mentoring less experienced engineers in a fast-paced environment requires not just technical skills, but also exceptional communication and time management prowess.

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Common Interview Questions for Staff Data Engineer - Insurance Data
Can you describe your experience with data pipeline development?

When answering this question, focus on specific projects where you've designed or optimized data pipelines. Highlight the tools and technologies you've worked with, and how your solutions enhanced data processing efficiency or quality.

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How do you ensure data quality and integrity in your projects?

Discuss your approach to maintaining data quality, mentioning practices such as validation checks, automated testing, and correction methodologies you’ve implemented in past roles to ensure data accuracy.

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What is your experience working with Databricks?

Prepare to share your hands-on experience with Databricks, including how you’ve utilized it for data modeling and pipeline creation. Provide specific examples of results you've achieved using this platform to support your answer.

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How do you lead and mentor junior data engineers?

Discuss your leadership philosophy and provide examples of how you’ve successfully mentored colleagues. Highlight any specific mentoring techniques or resources you've utilized to promote their development.

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What strategies do you use to manage cross-functional project teams?

Talk about your experience leading project teams, focusing on your communication skills, the importance of collaboration, and how you facilitate relationships between technical and non-technical team members for successful project outcomes.

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Can you give an example of a challenging project you’ve worked on?

Share a compelling story about a difficult project, emphasizing the challenges you faced and how you overcame them. Be sure to include the specific outcomes or successes resulting from your efforts.

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How do you stay up-to-date with the latest trends in data engineering?

Discuss the resources you use for ongoing learning, such as attending conferences, following industry leaders on social media, or participating in online courses. Express your commitment to maintaining relevant knowledge in a rapidly changing field.

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What tools do you prefer for data documentation and why?

Share your preferred tools for documenting data assets, such as metadata catalogs or diagramming software. Explain why you find these tools effective for maintaining clarity and ensuring accessibility for your team.

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How do you handle ambiguous requirements in projects?

Explain your approach to clarifying ambiguous requirements, such as involving stakeholders in discussions to accurately capture needs and the iterative processes you employ to refine project scopes and goals.

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Why do you think security and compliance are essential in data engineering?

Emphasize the importance of security and compliance in protecting sensitive data, particularly in the insurance sector. Share any experience you have with regulations like GDPR or CCPA to highlight your awareness of legal obligations in data handling.

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Kin is the home insurance company built for the future. By leveraging thousands of property data points, Kin customizes coverage and prices through a super simple user experience.

102 jobs
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BADGES
Badge ChangemakerBadge Diversity ChampionBadge Flexible CultureBadge Future Maker
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Life insurance
Disability Insurance
Commuter Benefits
Flexible Spending Account (FSA)
Education Stipend
Learning & Development
401K Matching
Paid Time-Off
Some Meals Provided
Snacks
Onsite Gym
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
April 3, 2025

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