Lead, scale, and mentor a large, multi-disciplinary data Team, establishing engineering excellence, consistent standards, and modern best practices across multiple sub-teams.
Define and execute the enterprise data Technology Roadmap, transitioning infrastructure into scalable cloud environments (AWS) and modern platforms (Lakehouse/ data Warehouse).
Drive the organization's data Governance framework, ensuring top-tier data quality, comprehensive metadata management, data lineage, and regulatory compliance.
Optimize data ingestion, movement, and Storage infrastructures, implementing High Availability (HA) mechanisms to reduce turnaround times and ensure seamless data accessibility.
Partner with cross-functional research and innovation teams to deliver high-quality, secure data products that empower Advanced Analytics, ML, and NLP & LLM initiatives.
Lead and support the delivery of data services for clinical and medical research activities, including complex data extraction, cohort identification, and preparation of research-ready datasets.
Collaborate closely with physicians, researchers, epidemiologists, and biostatisticians to translate research questions into scalable data solutions and analytical datasets.
Establish methodologies and standards for medical research data retrieval, ensuring accuracy, reproducibility, traceability, and compliance with privacy and regulatory requirements.
Requirements: Education: Bachelors degree in Computer Science, Software Engineering, Information Systems, or related field (Masters - an advantage).
Management Experience: 3+ years managing large technology teams or multiple data functions in large-scale environments.
Professional Experience: 5+ years in data domains ( data Engineering, data Platforms, BI ).
Technical Skills: Deep proficiency in SQL and Python, with hands-on experience in AWS and modern data Platforms.
Domain Expertise: Proven experience working with healthcare, clinical, or real-world medical data and governance/privacy frameworks.
Tech Capabilities: Familiarity with NLP, LLMs, Machine Learning technologies, and BI /Analytics tools.
Advantages
Hands-on experience supporting clinical/epidemiological research (complex SQL for medical research, cohort building, longitudinal databases).
Familiarity with healthcare interoperability standards and coding systems (ICD, SNOMED CT, LOINC, HL7/FHIR).
Deep understanding of healthcare data privacy and security regulations for research.
Join our exceptional team and play a key role in advancing global health research and innovation.
*
This position is open to all candidates.