Senior Analytics Engineer
Connie HealthWe are looking for a Senior Analytics Engineer to own our data transformation layer end-to-end. You will build the clean, well-modeled, documented datasets that the entire company relies on, spanning board-level book-of-business reporting (policy count, retention, effectuation, commissions), stakeholder self-service through Looker, and AI-driven exploration through tools like Claude. This is a high-leverage senior IC role: the quality of our analytics, forecasts, and operating decisions all depend on the foundation you build. You'll partner directly with Engineering, Finance, and Operations to fix data quality at the source, not downstream.
Tech stack: SQL, dbt, Redshift, Postgres, Looker (+ LookML), Fivetran, Airflow, Salesforce
We're looking for 5+ years in analytics/data engineering, deep hands-on dbt experience, strong SQL, and a track record of turning messy datasets into a trusted single source of truth. Bonus points for retention/lifecycle modeling, Looker administration, prepping datasets for AI consumption, or Medicare/insurance experience.
This is a hybrid position in our new Boston office near South Station, so local candidates only please. Unfortunately we are unable to do visa sponsorships at this time. Apply: https://recruiting.paylocity.com/recruiting/jobs/Details/422...
I am Huan, CTO at Connie Health. If you are interested, please feel free to reach out to me directly with your resume: huan.lai (at) conniehealth.com !
Opens the company's application page
Listed via
Findwork
findwork.dev
Similar roles
Design & Tech
Related reads from TCHNX

The Inference Economy: Why AI’s Biggest Cost Shift Is Happening After Training
A major shift in AI economics is reshaping the industry. As training frontier models becomes more expensive and inference becomes dramatically cheaper, companies are being forced to rethink how they build, deploy, price, and monetise intelligent systems.

The Emergence of Small Language Models: Why Efficiency Is Overtaking Scale
As the AI industry confronts computational costs and environmental concerns, a new generation of compact models is proving that bigger isn't always better. Small language models are reshaping enterprise AI deployment.

Algorithmic Bias in Design Systems: Why Your AI-Generated UI Might Exclude Users
As AI tools increasingly generate interface components, they're embedding biases that systematically exclude users. Understanding how machine learning models inherit prejudice is essential for creating truly inclusive design systems.

