Senior Data Engineer - Harbor Data Systems (HDS)

Harbor Health • Austin, TX

7d

About The Position

Harbor Health is rebuilding the operating system of healthcare. The HDS team contributes to this by building "HarborOS", the central nervous system of our clinical operations, tying together information from different clinical sources to drive optimal outcomes for our members. Data is our product.
We are looking for Analytics Engineers to build and our data ingestion layer to bring in the data that will help us transform healthcare. You will not just move data, you will convert it into actionable insights to help our clinic network change lives. You will take raw chaos (claims, ADT, clinical data) and architect the trusted data marts that power out patient care, risk adjustment, and financial decisions.

Requirements

• SQL Mastery: You can write performant, readable, and complex SQL. You understand window functions, CTEs, and the difference between a LEFT JOIN and a CROSS JOIN intuitively.
• dbt Fluency: You have used dbt in production. You understand incremental models, snapshots, and how to structure a project for scale.
• Python Literacy: You can read and understand Python scripts. You may not build the ingestion framework from scratch, but you can debug a transformation script if needed.
• Data Warehouse Fundamentals: You understand how column-oriented databases (Snowflake) work and how to write queries that prune partitions effectively.

Nice To Haves

• You bring deep subject matter expertise in healthcare data domains. You are fluent in processing 837 files, modeling the claim lifecycle (Adjudication, Reversal, Denial), and handling provider data nuances (NPI vs. TIN).
• Proven experience designing Dimensional Models (Kimball/Star Schema) from scratch. You know when to denormalize for performance and when to normalize for integrity.

Responsibilities

• Build the Semantic Layer: Design and implement production-grade dbt models that transform raw source data into clean, documented, and tested Data Marts.
• Enforce Data Quality: Move beyond basic NOT NULL checks. Implement semantic validation rules (using dbt tests or Great Expectations) that catch business logic failures before they hit the dashboard.
• Own the Pipeline: Manage the lifecycle of your data models from IDE to production, including code review, CI/CD integration, and performance tuning in Snowflake.
• Bridge the Gap: Collaborate with Platform Engineers to understand upstream ingestion patterns (Python/Fivetran) and debug data issues at the source.
• Design the core Star Schemas and data models that define our business. You will decide how we model complex concepts like "Attribution," "Risk," and "Claims Adjudication" to ensure historical accuracy and query performance.
• Act as the primary interface between Clinical Operations and Engineering. You will interview stakeholders to uncover the "Why" behind their requests and translate vague business needs into precise technical specifications.
• Mentorship & Standards: Set the standard for SQL style, dbt macro usage, and testing rigor. Mentor intermediate engineers on healthcare domain nuances (e.g., why a reversal claim behaves differently than a void).

Benefits

• Opportunity to shape the financial foundation of an innovative healthcare model
• Collaborative and dynamic work environment
• An organization made of people who are passionate about changing the healthcare landscape
• Competitive salary, company equity and robust benefits package
• Professional development and growth opportunities
• A transparent and unique culture

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1-10 employees