Location: Chicago, Illinois /
Remote Business Unit: Rush Medical Center
Hospital: Rush University Medical Center
Department: Data Management
Work Type: Full Time (Total FTE between 0.9 and 1.0)
Shift: Shift 1Work Schedule: 8 Hr (7:00:00 AM - 3:00:00 PM)
Pay Range: $50.68 - $75.51 per hour
Rush salaries are determined by many factors including, but not limited to, education, job-related experience and skills, as well as internal equity and industry specific market data. The pay range for each role reflects Rush's anticipated wage or salary reasonably expected to be offered for the position. Offers may vary depending on the circumstances of each case.
Summary:Join Rush as an
Enterprise Data Platform Lead (Data Governance & MDM) and play a pivotal role in shaping the future of enterprise data management across one of the nation's leading academic health systems. In this highly visible leadership role, you will guide the design, implementation, and evolution of modern data governance, master data management (MDM), data lifecycle management, and cloud-based data platform solutions that support clinical care, research, education, and business operations across the Rush University System for Health.
As a hands-on technical leader, you will mentor a team of data engineers, analysts, and developers while partnering closely with business leaders, data stewards, and technology teams to ensure enterprise data is accurate, trusted, secure, and accessible. You will drive strategic initiatives involving Microsoft Fabric, Azure OneLake, Informatica IDMC, data governance, data quality, and advanced data integration solutions that enable data-driven decision making throughout the organization.
The ideal candidate combines deep technical expertise with strong leadership skills and thrives in complex environments where healthcare, academia, research, and technology intersect. Experience supporting data management initiatives within an academic medical center, university health system, or similarly complex healthcare organization is highly valued.
This is an exciting opportunity to influence enterprise data strategy, establish best practices for data governance and lifecycle management, and help advance Rush's mission of excellence in patient care, education, research, and innovation.
Responsibilities:
- Manage a team of data specialists responsible for data governance and data lifecycle management functions.
- With Data Management teams and business counterparts, design and develop master data management solutions using MDM.
- With Data Management teams and business counterparts, implement and configure MDM workflows and processes.
- Work with business stakeholders to understand data requirements and ensure solutions meet those needs.
- Collaborate with data governance teams to establish and enforce data management policies.
- Perform data quality assessments and implement data cleansing processes.
- Ensure data consistency, accuracy, and integrity across all systems and applications.
- With Data Management teams and business counterparts, document all Data Platform, Lifecycle Management and 3rd party data management solution implementations, integrations, workflows, processes, configurations, and changes.
- With Data Management teams and business counterparts, provide training and support to business users on MDM tools and best practices.
- With Data Management teams and business counterparts, provide ETL-based dimensional modelling, data profiling, standardization, de-duplication, and cleansing.
- Deploy best practices to enhance system performance.
- Translate business requirements into technology solutions and collaborate with business and other technical teams.
- With Data Management teams and business counterparts, responsible for design, development and maintenance of data pipelines to enable data analysis and reporting.
- With Data Management teams and business counterparts, builds, evolves, and scales infrastructure to ingest, process and extract meaning out data.
- Write complex SQL queries or python code to support analytics needs.
- Lead projects / processes, working independently with limited supervision
- Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses.
- With Data Management teams and business counterparts, builds data infrastructure and determines proper data formats to ensure data is ready for use.
Required Job Qualifications:- Bachelor's degree.
- One to three years of technical lead skills
- Five years' experience with modern MDM tools
Preferred Job Qualifications:- Informatica IDMC certifications.
- Microsoft Data Fabric with Azure OneLake and Data Factory experience and/or certifications.
- 3+ years of hands-on data modeling, data integration, and data quality management experience.
- Ability to mentor and lead engineers in a hands-on capacity.
- 3+ years hands-on with DAMA-DMBOK Data Lifecycle Management (DLM).
- Experience with modern and legacy cloud and on-premises data storage technologies.
- Perform data quality assessments and implement data cleansing processes.
- Experience with developing and executing test plans for MDM solutions.
- Experience in Informatica IDMC with iPaaS, Customer 360 SaaS MDM, CLAIRE using Copilot, and CDGC or similar tools.
- Experience designing and implementing data management solutions in Informatica on Azure Data Fabric platforms.
- Familiarity with Informatica's implementation of the EDM Council's CDMC framework.
- Strong background in cloud computing, software engineering and data processing.
- Data management experience.
- Experience in ETL Tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka and Apache Camel.
- Experience designing and implementing analysis solutions on Azure OneLake and Microsoft Fabric
- Data Platform or Spark based platforms such as Databricks.
- Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL etc.
- Strong analytical and problem-solving skills.
- Strong verbal and written communication skills.
- Proficient programming skills in Python, SQL, NoSQL, and Spark.
- Ability to manage multiple projects is essential.
- Ability to work independently or in groups.
- Ability to prioritize time.
- Ability to adapt to a rapidly changing environment.
