Senior Analytics Engineer

Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America.

We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well‑being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands.

Clarus, a Doubtless company, is a pioneering pet health technology company transforming the future of pet healthcare. We develop connected solutions across the pet health landscape, helping veterinary teams and pet owners make more informed care and financial decisions. Together, we are reducing complexity and helping more pets receive the care they need.

Clarus is seeking an experienced Analytics Engineer to join the Analytics team. This individual will own the analytics engineering process and serve as the technical bridge between Data Engineering and Analytics delivery. They will build, expand, and optimize Clarus’s analytics architecture and pipelines, improving how data flows from diverse sources to downstream analytics solutions. In this role, you will lead high-impact data product and solutions initiatives from ambiguous problem definition through technical design, implementation, rollout, and adoption.

You will transform raw and curated data into reliable, analytics-ready models and consistent business metrics using dbt, SQL, Python, and Databricks, while establishing a scalable architecture and strong engineering practices.

The ideal candidate is a seasoned analytics engineer with strong data-wrangling skills and a passion for building and optimizing scalable analytics systems. They are self-directed, comfortable supporting multiple projects, systems, and products, and able to set technical direction while remaining deeply hands-on.

• Own analytics engineering work, including its roadmap, priorities, standards, and operating practices.
• Design and evolve analytics architecture, with clear responsibilities and quality expectations across bronze, silver, and gold data layers.
• Build, maintain, and optimize dbt models that transform source data into curated, reusable, analytics-ready datasets.
• Write and optimize advanced SQL, and use Python for data transformation, validation, automation, and complex processing where appropriate.
• Develop dimensional and business-oriented data models that support dashboards, self-service analysis, operational reporting, and data products.
• Establish and document shared KPI definitions, calculation logic, data contracts, ownership, and authoritative sources.
• Implement automated tests, source freshness checks, documentation, lineage, and monitoring to make data quality visible and dependable.
• Establish disciplined development practices, including Git-based version control, code review, CI/CD, and controlled promotion across environments.
• Partner with Data Engineering on ingestion, source schemas, platform performance, and reliable handoffs between foundational and analytical data layers.
• Partner with analysts, BI developers, and business stakeholders to translate requirements into scalable models rather than one-off reporting logic.
• Improve Databricks performance and cost efficiency through thoughtful table design, incremental processing, query optimization, and compute usage.
• Lead data-quality investigations, root-cause analysis, remediation, and communication when critical…