Principal Data Engineer

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?

As a key member of our data engineering department, you will lead the design, development, and implementation of data-centric solutions to drive actionable insights and enhance decision-making processes. Leveraging your expertise in data engineering, infrastructure and governance frameworks, you will collaborate with cross-functional teams to architect scalable and efficient data pipelines, optimize data storage and retrieval systems, and ensure data quality and integrity throughout the data lifecycle.

A day in the life could include…

• Lead the overall data architecture design, including ingestion, storage, management, and machine learning engineering platforms.

• Implement the architecture and create a vision for how data will flow through the organization using a federated approach.

• Manage data governance across multiple systems: data mastering, metadata management, data definitions, semantic-layer design, data taxonomies, and ontologies.

• Architect and deliver highly scalable, flexible, and cost-effective enterprise data solutions that support the development of architecture patterns and standards.

• Help define the technology strategy and roadmaps for the portfolio of data platforms and services across the organization.

• Ensure data security and compliance, working within industry regulations.

• Design and document data architecture at multiple levels across conceptual, logical, and physical views.

• Provide “hands-on” architectural guidance and leadership throughout the entire lifecycle of development projects.

• Translate business requirements into conceptual and detailed technology solutions that meet organizational goals.

• Collaborate with other architects, engineering directors, and product managers to align data solutions with business strategy.

• Lead proof-of-concept projects to test and validate new tools or architectural approaches.

• Stay current with industry trends, vendor product offerings, and evolving data technologies to ensure the organization leverages the best available tools.

• Cross-train peers and mentor team members to share knowledge and build internal capabilities.

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

• 10+ years of experience in designing & architecting data systems, warehousing and/or ML Ops platforms

• Proven experience in the design and architecture of large-scale data systems, including lakehouse and machine learning platforms, using modern cloud-based tools

• You can talk the talk and walk the walk! Can communicate effectively with executives and team

• Architect and implement solutions using Databricks for advanced analytics, data processing, and machine learning workloads

• Expertise in data architecture and design, for both structured and unstructured data. Expertise in data modeling across transactional, BI and DS usage models

• Fluency with modern cloud data stacks, SaaS solutions, and evolutionary architecture, enabling flexible, scalable, and cost-effective solutions

• Expertise with all aspects of data management: data governance, data mastering, metadata management, data taxonomies and ontologies

• Expertise in architecting and delivering highly-scalable and flexible, cost effective, cloud-based enterprise data solutions

• Proven ability to develop and implement data architecture roadmaps and comprehensive implementation plans that align with business strategies

• Experience working data integration tools and Kafka for real-time data streaming to ensure seamless data flow across the organization

• Expert