We are looking for a highly skilled Data Engineer with Real World Data (RWD) experience to build and manage end-to-end data pipelines for multimodal healthcare datasets. The ideal candidate will work at the intersection of data engineering, analytics, and healthcare research, transforming complex healthcare data into analysis-ready assets that support advanced analytics, AI/ML initiatives, and evidence-generation studies.

This role requires expertise in large-scale healthcare data processing, data harmonization, cloud platforms, and modern data engineering practices.

Responsibilities

Data Engineering & Pipeline Development

- Design, develop, and maintain scalable ETL/ELT pipelines for large healthcare and real world datasets.
- Build and manage data ingestion, transformation, harmonization, and analytics layers.
- Implement data quality frameworks, governance controls, lineage tracking, and monitoring.
- Manage data lifecycle processes across raw, curated, and analytics-ready environments.
- Work with structured and unstructured healthcare datasets from multiple sources.

Healthcare Data Harmonization

- Harmonize heterogeneous healthcare data sources and coding systems into standardized formats.
- Map and transform clinical terminologies including

o SNOMED CT

o ICD-10

o LOINC

o RxNorm

o CPT/HCPCS

- Support implementation of common data models such as OMOP and FHIR.

Analytics & Study Support

- Support data feasibility assessments and data quality evaluations.
- Collaborate with epidemiologists, biostatisticians, data scientists, and business stakeholders.




- Develop reusable data assets, cohorts, and model-ready datasets.
- Enable advanced analytics and AI/ML use cases through reliable data engineering practices.

Application & Platform Development

- Contribute to analyst-facing applications, dashboards, and self-service data products.
- Support development of data products using modern workflow automation and AI assisted engineering approaches.
- Provide guidance on efficient querying and optimization of large longitudinal datasets.

Requirements

Data Engineering

- Strong experience with Python, SQL, Spark / PySpark
- Experience building production-grade ETL/ELT pipelines.
- Strong understanding of data modelling concepts - Star schema, Snowflake schema, Normalization and denormalization
- Experience with metadata management, lineage, monitoring, and data governance.

Platforms & Technologies

Experience in one or more of the following - Palantir Foundry, Databricks, Snowflake, AWS or equivalent cloud platforms, HPC environments

- Containerized workloads Software Engineering Practices
- Git
- CI/CD pipelines
- Unit testing and automation
- Performance monitoring and optimization

Domain Expertise





Candidates should have working knowledge of Healthcare Real World Data (RWD), Claims data, Electronic Health Records (EHR), Registries, Patient-reported outcomes, Wearables and digital health datasets

Understanding of study feasibility, observational research, and healthcare analytics workflows is highly desirable.

AI & Automation Experience

Preferred experience with Large Language Models (LLMs), AI-assisted data engineering, Agentic workflows, Data profiling and automated data quality assessments, integration of ML outputs into production data pipelines

Qualification / Requirement

- 4-8 years of experience in data engineering, healthcare analytics, or real-world data platforms.
- Experience working with large-scale healthcare datasets in regulated environments.
- Robust problem-solving and analytical skills.
- Excellent stakeholder communication capabilities.
- Formal educational qualifications are flexible; relevant experience and expertise are valued.

Nice to Have

- Experience with multimodal healthcare datasets (clinical, omics, imaging, genomics, proteomics, microbiome, etc.).
- Hands-on experience implementing OMOP/FHIR at scale.
- Experience building self-service applications and data products for business users.
- Familiarity with federated data networks and data quality frameworks.

What We're Looking For

- Systems thinker who can work with complex and evolving datasets.
- Strong collaboration skills across technical and business teams.
- Agile mindset with a focus on delivery.
- Commitment to data privacy and ethics.

📌 Senior Data Engineer - Real World Data & Healthcare Analytics (Chennai)
🏢 Zifo
📍 Chennai