Senior Data Analyst

🏢 Doma · all 3 jobs
📍 United States
💰 USD 92,000 - 120,000 / annual
📅 Posted Sep 10, 2026 · via Himalayas
🏷 Data Analyst, Business Intelligence, Bi Engineering, Data Engineering, Senior Data Analytics, Senior Level Data Analyst +6 more
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If you’re good at what you do, you can work anywhere. If you’re the best at what you do, come work for Doma Technology.

About Us 

Doma Technology LLC offers solutions for lenders, real estate professionals, title agents, and homeowners that make closings vastly simpler and more efficient, reducing cost and increasing customer satisfaction.

Our Values

- Obsessively Entrepreneurial - We encourage calculated risk-taking, and we know that some of our best learning happens by making mistakes along the way.

- People First - We communicate with honesty and respect to our customers, colleagues, and partners.

- Better Together - We believe diversity, equity and inclusion creates value through the differences in our backgrounds, experiences, and perspectives.

- Act with Integrity - We hold ourselves to the highest ethical standards in all of our business practices.

Doma is looking for a Senior Data Analyst to own and evolve Looker, the business intelligence platform our Operations teams rely on for real-time, day-to-day reporting — SLAs, exception management, escalations, hands-on time reporting, turnaround times, vendor management, and more. You’ll be the primary point of contact for Looker across the company: owning the connectivity between Snowflake and our other source data and Looker end-to-end, building and maintaining the dashboards that keep Operations running, safeguarding data quality and provenance, and partnering with Finance, Data Science, and other business units on their reporting needs. We’re also looking for someone excited about what comes next — ideally with experience building or working hands-on with AI/agentic reporting tools — to help us build an agentic reporting layer on that same underlying data so business users can self-serve ad hoc questions that don't require long term dashboards.

You're fired up to:
• Use your raw data analysis intuition to revolutionize a 150-year-old industry
• Own, build, and maintain the Looker dashboards and data models that Operations, Finance, and Data Science depend on every day
• Own the connectivity between Snowflake and other source data and Looker — the pipelines, data models, and integrations that keep our reporting layer accurate and current end-to-end
• Be the primary point of contact for Looker company-wide — fielding requests, triaging issues, and setting standards for how dashboards get built
• Oversee data quality and data provenance across our reporting layer
• Play a key role in day-to-day operational decision-making — SLAs, exception management, escalations, hands-on time reporting, turnarounds, and vendor management — through rapid delivery of insights
• Design and help build an agentic reporting layer on top of our existing data — working hands-on with AI reporting agents so business users can self-serve ad hoc requests instead of filing a ticket
• Learn and leverage the ins and outs of a complex, valuable problem domain in title insurance and real estate

You definitely have:
• 3-5 years contributing to data analytics, business intelligence, or data science projects, ideally across a variety of professional contexts (e.g. start-ups and large companies, or consumer- and business-facing applications)
• Professional experience using Looker — LookML, dashboard design, and data modeling
• Ability to write complex SQL joins in your sleep
• Professional experience writing code with proficiency in Python, git, and similar tools
• Ability to communicate technical concepts to people throughout the company, including business partners in Operations, Product, and senior leadership
• Strong opinions, loosely held, about all things data

You might even have:
• Ideally, hands-on experience building, configuring, or working with AI/LLM-based reporting agents or similar agentic analytics tooling — prompt design, pipeline setup, and keeping an agent grounded in accurate underlying data
• Experience owning data pipelines or connectivity between a warehouse (e.g. S

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