Data Engineer

Health Partners is hiring a Data Engineer to help expand and scale the data foundation that powers pharmacy analytics, reimbursement strategies, and critical business decisions.

At Health Partners, our mission is to make healthcare more affordable and accessible through smarter use of data. We are looking for an Engineer who thrives on solving complex data challenges and building reliable, scalable data solutions.

As part of the Care Delivery Pharmacy Data Team, you will design, build, and optimize data pipelines and products that transform pharmacy, claims, pricing, cost, and reimbursement data into trusted assets for analytics and decision-making. Collaborating closely with analysts, engineers, and business partners, you will improve data quality, automation, reliability, and accessibility while applying modern data engineering practices.

Your work will support initiatives including prescribing trend analysis, 340B program optimization, reimbursement analytics, payer contracting strategies, purchasing decisions, and executive reporting. By accelerating the integration and analysis of complex pharmacy data, you will help uncover opportunities, manage costs, and support informed decision-making across the organization.

Reporting to the Senior Manager of Health Informatics, you will join a collaborative team consisting of one Senior Data Engineer and two Data Analysts. We work using Agile practices and partner closely with pharmacy, informatics, finance, and operational leaders to deliver incremental value through iterative delivery, continuous improvement, and shared ownership. This role adds critical engineering capacity to support a growing portfolio of pharmacy analytics initiatives.

• Bachelor's degree in Computer Science, Data Science, Social Science, Operations Research, Statistics, Applied Mathematics, Econometrics, or another quantitative field with four (4) years of experience in business analytics, data science, software development, data modeling, and/or data engineering, OR a Master's degree in Computer Science, Software Engineering, Mathematics, or a related field.
• Two (2) years of experience in a hands‑on data engineering role.
• Two (2) years of experience working with SQL and Python.
• Two (2) years of experience working with modern big data platforms such as:
  Azure Data Factory, Azure Synapse, PowerBI, Databricks, or similar.
• Knowledge of data modeling concepts and techniques, including star and snowflake schemas, denormalized data models, and third normal form (3NF).
• Understanding of common data formats, including Parquet, CSV, and JSON.
• The following qualifications are considered critical to success in this role. Candidates should have substantial, demonstrated experience in these areas.
  • Knowledge of data processing methodologies, including batch processing, time-based partitioning, distributed processing, and real-time data streaming.
  • Strong data profiling, analytical, and critical thinking skills, with the ability to identify patterns, trends, and opportunities within complex datasets.
• Experience with version control and CI/CD practices;
  Git experience preferred.
• Self‑motivated, curious, and creative, with the ability to work independently and take initiative.
• Strong verbal and written communication skills, with the ability to effectively partner with business stakeholders, end users, and technical teams.
• Demonstrated ability to collaborate effectively within diverse, cross‑functional development and operations teams.

• Experience working in Agile and Scrum-based development environments.
• Experience working in a public cloud infrastructure.
• Interest in advancing Data Ops practices, including CI/CD, Infrastructure as Code (IaC), automated testing, and configuration management.
• Knowledge of healthcare operations, healthcare data, and payer or care delivery processes.
• Proven ability to collaborate effectively with product managers, program managers, engineers, and business stakeholders.
• Strong analytical, problem‑solving, and critical thinking skills.
• Demonstrated ability to influence without direct authority and succeed in a fast‑paced, evolving environment.
• Ideal candidates will have expertise in one or more of the following areas:
  • Relational databases, including Oracle and Microsoft SQL Server.
  • SQL and Oracle performance tuning, query optimization, stored procedures, and triggers.
  • CI/CD, continuous testing, and site reliability engineering (SRE) practices.
  • Microsoft Azure…