MTQIP Clinical Registry Data Engineer

The Michigan Trauma Quality Improvement Program, or MTQIP, is a statewide quality improvement collaborative focused on improving trauma care, outcomes, and data-driven performance across participating Michigan trauma centers.

MTQIP is seeking a Clinical Registry Data Architect to support clinical registry data infrastructure, report exports, data pipelines, automation, and program-wide technical data needs. This position will play a key role in maintaining and improving SQL-based report exports from registry platforms, including Snowflake Reader, and supporting the development of streamlined workflows for data submission, validation, reporting, and analysis. In addition, MTQIP is looking to develop extracts from electronic medical record such as EPIC Clarity, and proficiency in data science concepts such as Large Language Models (LLM).

This role is well suited for a data professional who enjoys working at the intersection of healthcare, technology, quality improvement, and applied data engineering. The ideal candidate will be comfortable working with complex clinical data, translating registry and measure specifications into technical logic, writing and maintaining SQL, supporting data quality checks, and collaborating with clinical, operational, and technical stakeholders.

Key Responsibilities

• Develop, maintain, and troubleshoot SQL-based data exports from clinical registry systems, including Snowflake Reader.
• Translate registry specifications, data dictionary requirements, and performance measure logic into reproducible SQL queries and export processes.
• Support the development, maintenance, and documentation of MTQIP data pipelines, including data extraction, transformation, validation, and reporting workflows.
• Create and maintain automated processes to reduce manual data handling, improve reproducibility, and streamline recurring report production.
• Provide global MTQIP technical data support across registry reporting, collaborative performance measurement, data validation, vendor data workflows, and internal analytic needs.
• Support ad hoc technical and data projects, including one-time data extracts, special analyses, data investigations, process improvement efforts, and emerging MTQIP reporting priorities.
• Work with complex healthcare datasets, including trauma registry data, hospital-submitted data, vendor registry data, and potentially electronic health record data from Epic or related systems.
• Support clinical registry submission workflows, including mapping, formatting, validation, and preparation of data for reporting and analysis.
• Partner with clinicians, program staff, analysts, vendors, and institutional technical teams to understand data needs and convert them into scalable technical solutions.
• Perform data quality checks to identify missing, inconsistent, duplicated, or unexpected values.
• Document SQL logic, data sources, transformation rules, data validation steps, and recurring operational workflows.
• Support the creation of standardized datasets for internal analysis, quality improvement reporting, external submission, and collaborative performance measurement.
• Assist with troubleshooting data discrepancies between registry systems, exported files, analytic datasets, and measure specifications.
• Participate in planning for data infrastructure improvements, report automation, and long-term data modernization efforts.
• Communicate technical concepts clearly to both technical and non-technical stakeholders.

Minimum Qualifications

• Bachelor's degree in information systems, computer science, data science, health informatics, statistics, engineering, or a related field, or an equivalent combination of education and experience.
• At least 3 years of experience in data engineering, database programming, systems analysis, health informatics, analytics programming, or related technical work.
• Demonstrated experience writing, debugging, maintaining, and optimizing SQL queries, stored procedures, functions, views, or similar database objects.
• Experience working with relational databases, data warehouses, or cloud-based data platforms.
• Experience developing or supporting ETL, ELT, data extraction, data transformation, or recurring data export processes.
• Experience with data cleaning, data validation, and data quality review.
• Ability to translate business, clinical, operational, or registry requirements into technical specifications and reproducible data logic.
• Demonstrated ability to document technical workflows, data definitions, code logic, and validation steps.
• Demonstrated ability to communicate complex technical concepts clearly to technical and non-technical audiences.
• Strong attention to detail, problem-solving ability, and commitment to producing accurate, reliable, and reproducible data outputs.
• Ability to work both independently and collaboratively in a mission-driven, quality improvement-focused environment.

Desired Qualifications

• Experience with Snowflake, Snowflake Reader, or similar cloud-based data warehouse platforms.
• Experience with Epic, Clarity, Caboodle, or other electronic health record data sources.
• Experience working with clinical registry data, trauma registry data, quality improvement data, or hospital administrative data.
• Experience with healthcare data standards, clinical data dictionaries, registry submission requirements, or measure specifications.
• Experience with Python, R, Stata, SAS, or another statistical or programming languages used for data transformation, automation, or analysis.
• Experience with process automation, scheduled jobs, file transfer workflows, APIs, or other recurring data movement processes.
• Experience supporting ad hoc technical projects, data investigations, and stakeholder-driven analytic requests.
• Experience using version control tools such as Git.
• Experience creating reusable, well-documented reporting datasets.
• Familiarity with healthcare quality improvement, trauma care, collaborative quality initiatives, or clinical performance measurement.
• Experience working with vendors, external partners, hospital data teams, or multidisciplinary clinical stakeholders.
• Knowledge of HIPAA, data privacy, data security, and appropriate handling of protected health information.