Principal Data Engineer (RWE)
Veramed (company site, opens in a new tab)RemoteDirect career pageEst. 30–45 LPA
Posted on 21 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and automate patient-level data products for use in dashboards, reports, and studies supporting Real World Evidence (RWE) initiatives.
- Transform heterogeneous raw healthcare datasets into reusable data models compliant with OMOP CDM standards and create FAIR, AI-ready data pipelines to enhance interoperability and analytics.
- Engage technically with stakeholders and internal teams to translate requirements into data structures, maintain documentation, validate data quality, and troubleshoot ETL issues.
Minimum Requirements
- Strong expertise in OMOP CDM version 5.4 or 6 and healthcare data models and terminologies such as SNOMED CT, RxNorm, ICD-10, LOINC, and HCPCS/CPT.
- Proven experience building scalable ETL/ELT pipelines using Databricks, PySpark, Spark SQL, SQL, Delta Lake, and working with large-scale healthcare datasets.
- Demonstrated skills in Power BI development, data modeling, automated data quality frameworks, and semantic data engineering with cloud-based platforms.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in Real World Data (RWD) and Real World Evidence (RWE) within healthcare, capable of assessing business needs and recommending appropriate datasets for analytical use cases.
- Technical proficiency in constructing FAIR-compliant, scalable data pipelines and producing AI-ready data products in cloud/distributed environments.
- Ability to collaborate with multi-disciplinary teams including epidemiologists, statisticians, and IT to create validated, documented, and interoperable data solutions for observational and epidemiological studies.