YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation.
At YASH, we’re a cluster of the brightest stars working with cutting‑edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.
Job Description
Experience - 7-10 years
Role: Senior Python Developer
Health Data Engineer - Data Nexus Platform
What You’ll Build
- Hospital data integration pipelines: Extract consented patient EHR data from European hospitals → pseudonymize → standardize to OMOP CDM
- OMOP CDM transformation logic: Map hospital diagnosis codes (ICD-10), lab results (LOINC), medications to OMOP standardized vocabularies (SNOMED-CT)
- Data quality validation framework: Implement 16-dimension data quality checks ensuring data completeness, accuracy, and regulatory compliance for FDA/EMA submissions
- Master data management (MPI): Patient identity resolution, entity matching, and deduplication across multiple hospital systems
- Clinical domain pipelines: Build ETL workflows for 8+ clinical domains including diagnoses, medications, lab results, procedures, clinical assessments, and biomarkers
- Regulatory-grade validation: Prove lossless transformation, maintain audit trails, and ensure GxP compliance for pharmaceutical regulatory submissions
Required Experience
- Healthcare Domain Expertise (Non-Negotiable)
- 5+ years working with hospital EMR/EHR systems (EPIC, Cerner, or similar)
- Hands-on OMOP CDM experience: Mapping hospital data to OMOP Common Data Model (PERSON, VISIT_OCCURRENCE, CONDITION_OCCURRENCE, DRUG_EXPOSURE, MEASUREMENT, etc.)
- Clinical coding systems: Deep familiarity with ICD-10, SNOMED-CT, and LOINC
- Master Data Management (MPI): Patient identity resolution, entity matching, deduplication, golden record creation
- Healthcare data standards: Working knowledge of HL7, FHIR, or EDI
- Real-world hospital data complexity: Understanding of incomplete records, coding variations, longitudinal patient journeys, and clinical workflows
Technical Skills
- Python + SQL: Advanced proficiency for ETL development, data transformation, and validation logic
- Data pipeline development: Building scalable, maintainable ETL/ELT workflows (pandas, PySpark, or similar)
- Data quality frameworks: Schema validation, referential integrity checks, reconciliation logic, null handling, data profiling
- Cloud platforms: Experience with cloud data infrastructure (AWS, GCP, Azure, or Oracle Cloud)
- Version control: Git-based development workflows
- Regulatory & Compliance Knowledge
- GxP awareness (preferred): Basic understanding of regulatory data requirements for pharmaceutical submissions
- Data governance: Lineage tracking, metadata management, audit trail documentation
Preferred Background
- Academic health informatics or biomedical informatics training
- Experience with oncology, immunology, or clinical research datasets
- Exposure to clinical trials data or pharmaceutical research
- Knowledge of European hospital systems or GDPR compliance
- Experience with data orchestration tools (Airflow, Azure Data Factory, etc.)
What We’re NOT Looking For
- Generic data engineers with only cloud platform experience
- Candidates who've only worked with clean, structured datasets
- ETL developers without healthcare domain knowledge
- Architects who talk conceptually but lack hands-on coding experience
Day-to-Day Responsibilities
- Write Python/SQL code to transform hospital EHR data into OMOP CDM format
- Map clinical codes (ICD-10 → SNOMED-CT, local lab codes → LOINC) using standardized vocabularies
- Implement data quality validation logic proving 100% data integrity for regulatory submissions
- Build patient identity resolution workflows across multiple hospital data sources
- Debug complex data quality issues in real-world hospital datasets (missing values, coding inconsistencies, schema variations)
- Document transformation logic, data lineage, and validation rules for audit compliance
- Collaborate with hospital partners to understand clinical workflows and data structures
- Support pharmaceutical clients in understanding data quality and OMOP standardization
At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.
Our Hyperlearning workplace is grounded upon four principles
- Flexible work arrangements, Free spirit, and emotional positivity
- Agile self-determination, trust, transparency, and open collaboration
- All Support needed for the realization of business goals,
- Stable employment with a great atmosphere and ethical corporate culture