Analytics Engineer: Shape the Trusted Healthcare Data Core

Sprinter Health; Menlo Park (CA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Meaningful pre-IPO equity

Medical, dental, and vision plans

Flexible PTO

401(k) with match

Parental leave

Relocation assistance

Job summary

Sprinter Health is seeking an Analytics Engineer to build the trusted data layer used by analysts, data scientists, operations, finance, and product teams. You’ll own canonical models, metric definitions, and transformation logic, ensuring data is reliable and reusable across the company.

You will model data in dbt or equivalent tooling, create reporting-ready tables, improve lineage, and document data contracts.

Qualifications

• Expert-level SQL and data modeling for reporting, analysis, and decision-making.
• Experience building analytics systems in production cloud warehouses.
• Familiarity with dbt or equivalent data transformation frameworks.

Responsibilities

• Build canonical data models creating a shared source of truth across the company.
• Define and maintain core business, operational, financial, product, and customer-facing metrics.
• Model data in dbt to enable dashboards and self-serve analytics.
• Write tests, documentation, and data quality checks to catch issues early.
• Define definitions for tables, fields, and metrics so teams understand data meaning.
• Reconcile metric definitions across internal teams and external reporting needs.
• Trace data lineage and debug dashboards, reports, or tables that change unexpectedly.
• Partner with analysts, data scientists, ops, finance, product, engineering, and customer teams to translate needs into reliable models.
• Help build reusable reporting frameworks to accelerate payer launches.
• Collaborate with data platform to evolve warehouse tables and improve data contracts.

Skills

SQL

dbt

Data modeling

Analytics engineering

Cloud data warehouse

Communication

Tools

dbt

BigQuery

Snowflake

Python

Job description

Sprinter Health is seeking an Analytics Engineer to build the trusted data layer used by analysts, data scientists, operations, finance, and product teams. You’ll own canonical models, metric definitions, and transformation logic, ensuring data is reliable and reusable across the company.

You will model data in dbt or equivalent tooling, create reporting-ready tables, improve lineage, and document data contracts.