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
• 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