Senior Data Modeling & Pipeline Engineer

Location: NYC, San Francisco, or Denver (4 days/week onsite) Compensation: $150–170K base Client: Fast‑growing healthcare insurance startup (data‑driven tech company at its core)

About the Role

Our client is a rapidly scaling healthcare insurance startup where data is the backbone of the business. The data team is lean — three people supporting 70+ engineers — and they’re looking for a hands‑on Data Modeling & Pipeline Engineer to build the foundational data layer powering customer‑facing reporting today and ML/AI products tomorrow.

You’ll take messy, complex production data and turn it into reliable, scalable models and pipelines. This role is ideal for someone who thrives in ambiguity, moves at startup speed, and can point to measurable impact in past roles.

What You’ll Own

• Build and mature the company’s core data models and pipelines

• Clean up and scale existing data infrastructure to support enterprise customer integrations

• Partner with product and operations to understand data needs and deliver accurate, trusted outputs

• Work directly with engineers to interpret complex production data and maintain accurate Metabase dashboards

• Improve data quality, governance, and reliability to enable future ML/AI products

• Ensure data models and pipelines are robust, scalable, and production‑ready

Must‑Haves (Dealbreakers)

• Experience building data models and pipelines at a VC‑backed startup or a modern tech company founded after 2005 (e.g., Stripe, Uber, Lyft, Datadog — FAANG does not count)

• Advanced SQL in complex, high‑volume production environments

• Willingness to work onsite 4 days/week in Denver, SF, or NYC

Baseline Qualifications

• 3–7 years in analytics or data science at a high‑growth company

• Bachelor’s degree in CS, Math, Engineering, or a hard science

• Hands‑on experience with Snowflake, BigQuery, or Redshift

• Ability to clearly articulate business impact with quantified outcomes

Nice‑to‑Haves

• Experience partnering with product and operations teams

• Background in regulated industries (fintech, insurance, logistics, shipping)

• Hands‑on dbt experience for production data modeling

• Familiarity with GCP/BigQuery, Python, or Terraform