Manager- Data Aggregation

We'll trust you to:

• Collect, clean, and aggregate patient-level data from Electronic Health Records (EHRs), lab systems, and external databases. 
• Apply tokenization techniques to replace direct identifiers while preserving data integrity for linkage and analysis. 
• Perform or support expert determination de-identification processes to evaluate and minimize re-identification risk in datasets. 
• Ensure all activities comply with HIPAA, and institutional privacy policies, particularly within HISEC environments 
• Manage and maintain secure data pipelines and repositories for sensitive patient information. 
• Assist in the development of standard operating procedures (SOPs) for secure data aggregation and handling. 
• Support the generation of anonymized datasets for research, analytics, or external data sharing initiatives. 
• Monitor data quality, flag inconsistencies, and ensure proper documentation of data provenance and transformation. 
• Provide support for audits, security assessments, and internal data governance reviews. 
• Design and implement end-to-end Data aggregation solutions tailored to business requirements using Python and Pyspark. 
• Synthesizes findings, develops recommendations, and communicates results to clients and internal teams. 
• Assumes project management responsibilities for Data aggregation implementation on each project with minimal supervision, including managing onshore/client communication, leading meetings, and drafting agendas 
• Manage multiple projects simultaneously while meeting deadlines 

You'll need to have:

• Engineering/Master’s Degree from a Tier-I/Tier-II institution/university in Computer Science or relevant concentration, with evidence of strong academic performance. 
• 6+years of relevant consulting-industry experience 
• Deep understanding of data management best practices, data modeling and data analytics 
• Strong understanding of U.S. pharmaceutical datasets and their applications 
• Experience with tokenization tools/methodsand expert determination for de-identification. 
• Logical thinking and problem-solving skills along with an ability to collaborate. 
• Familiarity with HISEC standards or other high-security frameworks 
• Strong programming skills in Python and working knowledge of PySpark. 
• Proficiency in Microsoft Office products,data analysis tools (e.g., Snowflake, Redshift) and job orchestration (Airflow, Databricks workflows) 
• Strong understanding of HIPAA, GDPR, and related data privacy regulations. 
• Excellent verbal and written communication skills, with the ability to convey complex information clearly to diverse audiences  
• Strong organizational abilities and effective time management skills 
• Ability to thrive in an international matrix environment and willingness to support US clients during US working hours with 3-4 hours of overlap.