Senior Data Engineer

Apricot Health•Oklahoma City, OK

About The Position

At Apricot, we believe that nurses are the unsung heroes of healthcare, and they deserve to be treated as such. Our goal is to empower nurses by freeing them from the shackles of paperwork, allowing them to focus on what they became nurses to do: take care of patients. Role Overview: We are looking for a Senior Data Engineer to own Apricot’s analytics foundation end-to-end. This role is responsible for designing, building, and evolving our data pipelines, medallion architecture (Bronze → Silver → Gold), and analytics models as our application, customers, and data volume scale. You’ll turn raw PostgreSQL application data into trusted, analytics-ready datasets in BigQuery that power: Omni Topics and semantic models Dashboards used across Product, CX, Ops, and Leadership Embedded analytics surfaced to customers This is not a back-office reporting role. You will be a builder, architect, and thought partner—working closely with Engineering and Product to ensure our data stays robust as schemas evolve and the product grows.

Requirements

Strong experience building analytics data pipelines (ELT) in a modern warehouse
Deep SQL expertise (BigQuery preferred): complex joins, window functions, performance tuning
Proven experience designing analytics-friendly data models
Hands-on ownership of production data workflows—not just analysis
Comfort working in ambiguity and making pragmatic architectural decisions
Experience defining metrics and maintaining a shared source of truth
Ability to design semantic layers and dashboards that real teams actually use
Strong instincts around data usability, not just correctness
Ability to explain tradeoffs and data meaning to non-technical stakeholders
Experience with BigQuery (or similar columnar warehouse)
Familiarity with dbt or equivalent transformation/testing patterns
Experience managing schema evolution and downstream impacts
Practical understanding of access controls and sensitive data handling

Nice To Haves

Omni experience (or similar semantic BI tools)
Python for data tooling, automation, or validation
Experience with embedded analytics
Familiarity with medallion or layered warehouse architectures
Healthcare or regulated-data experience

Responsibilities

Own the data platform & pipelines
Design and maintain ELT pipelines from PostgreSQL → BigQuery
Build and evolve a medallion architecture that is resilient to schema and product changes
Materialize clean, well-documented Silver and Gold tables for analytics use
Manage scheduling, freshness, and reliability of data transformations
Data modeling & analytics enablement
Define analytics-ready models that balance correctness, usability, and performance
Create and maintain semantic models / Topics in Omni
Ensure metric definitions are consistent, well-documented, and trustworthy
Partner with stakeholders to translate questions into durable data models
Dashboards & self-serve analytics
Build and maintain dashboards used by teams across the company
Support embedded analytics use cases for customers
Design dashboards that emphasize clarity, sensible defaults, and drill-downs
Enable teams to answer their own questions without constant rework
Data quality, governance, and scale
Implement guardrails for data quality, freshness, and definition drift
Monitor downstream impact of application schema changes
Apply PHI-safe practices and org-level access controls
Optimize BigQuery performance and cost (partitioning, clustering, materialization strategy)
Cross-functional collaboration
Work closely with Product and Engineering as the application evolves
Help shape analytics strategy—not just execute tickets
Serve as a thought partner on how data should be structured to support future use cases