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.
We are looking forward to hire Python Professionals in the following areas :
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
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
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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
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