The Data Steward & Data Operations Specialist ensures high-quality master supporting commercial operations across multiple systems in a pharma/life sciences environment. Along with core stewardship activities — processing data change requests, onboarding, enrichment, and data quality initiatives — this role also drives automation of MDM operations using Python and PySpark within Reltio MDM, reducing manual effort and improving data quality at scale.
Typical Accountabilities
- Process Data Change Requests related to HCP/HCO master data
- Conduct matching and merging of HCM records within Reltio MDM
- Monitor and process data queues across all object types in scope
- Identify, plan, and implement data quality initiatives
- Build automation scripts using Python/PySpark for data cleansing, matching, deduplication, and reporting
- Collaborate with Commercial business users on data availability, completeness, and quality needs
- Perform data completeness/quality assessments of external provider data
- Perform mass data uploads, cleansing, enrichment, and updates
- Perform analysis and maintenance for HCP/HCO data within Reltio MDM
- Cooperate with IT/Data Engineering on issue resolution and automation opportunities
- Conduct data investigations and matching across sources
- Provide reports/dashboards on data in scope, using Python/PySpark for automation where applicable
- Define and track KPIs and Data Quality Metrics; support junior team members
Essential
- 4–6 years of experience in Data Stewardship/Data Management Operations, preferably in Pharma/Life Sciences
- Hands-on experience with Reltio MDM (or similar MDM platform) for HCP/HCO data
- Working knowledge of Python and PySpark for automation and data pipelines
- Hands-on experience with AWS services (S3, Glue, SageMaker etc..)
- Familiarity with API-based integrations for MDM data exchange
- Solid understanding of data quality and data management principles
- Experience in data analysis and processing activities
- Advanced MS Excel and intermediate/advanced SQL knowledge
- High attention to detail; proactive, analytical, and investigative mindset
- Proven track record of process improvement, including automation of manual processes
- Strong written/verbal communication skills