Principal Data Engineer – RWE

Veramed

. Develop data processes for automated ongoing generation of patient-level data products for dashboards, reports, and studies .

Posted 9/21/2026full-timeRemote • IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Real World Data (RWD) and Real World Evidence (RWE) concepts, with strong capabilities in building scalable ETL/ELT pipelines and creating AI-ready datasets. Proficient in data validation, monitoring, and the development of FAIR-compliant data pipelines within healthcare data ecosystems.

Highest-signal resume keywords

Real World Data (RWD) ExpertiseOMOP CDM v5.4, v6 ProficiencyDatabricks and PySpark ExperienceFAIR Data Pipeline DevelopmentPower BI Development Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

ETL/ELT Pipeline DevelopmentData Validation and MonitoringHealthcare Data ModelingSemantic Data EngineeringData ProfilingSQL and Spark SQLAI-Ready Dataset CreationAutomated Data Quality FrameworksDelta LakeHealthcare Data Ecosystems

Soft Skills

Stakeholder ManagementCommunication SkillsCross-Functional Collaboration

Tools & Technologies

DatabricksPySparkPower BICloud-Based Data PlatformsDistributed Processing Frameworks

Industry Keywords

Real World Evidence (RWE)OncologyRespiratoryImmunology & InflammationInfectious DiseasesSNOMED CTRxNormICD-10LOINCHCPCS/CPT

Tech Stack

Tools & technologies

CloudETLPySparkSparkSQL

About the role

Key responsibilities & impact

Develop data processes for automated ongoing generation of patient-level data products for dashboards, reports, and studies
Manipulate datasets onboarded from data vendors and partners into usable structures for RWE studies, dashboards, and other outputs
Transform heterogeneous healthcare datasets into reusable data models for observational research and epidemiology studies
Convert bespoke datasets to OMOP format where appropriate and account for residual data that cannot be converted
Build FAIR data pipelines and semantic data engineering frameworks
Create AI-ready datasets supporting generative AI use cases
Engage with epidemiologists, statisticians, market access and health economists to scope requirements and translate needs into actionable data structures
Collaborate with the RWE programming team to build data structures and support study outputs
Liaise with IT to ensure inbound datasets are fit for agreed purposes
Liaise with technical staff from analysis software vendors such as Databricks
Maintain documentation of data flows, schemas, pipelines, and processes
Design and perform data validation and monitoring to ensure accuracy and reliability
Troubleshoot data loading, extraction, and transformation issues
Collaborate with three other Data Engineering team members and provide workload support as needed

Requirements

What you’ll need

Strong understanding of Real World Data (RWD) and Real World Evidence (RWE) concepts
Ability to assess business requirements and recommend appropriate real-world healthcare datasets for analytical use cases
Deep understanding of healthcare data models and healthcare data ecosystems
Strong expertise in OMOP CDM v5.4, v6, including extensions
Knowledge of SNOMED CT, RxNorm, ICD-10, LOINC, and HCPCS/CPT
Strong experience building scalable ETL/ELT pipelines
Expertise in Databricks, PySpark, Spark SQL, SQL, and Delta Lake
Experience working with large-scale healthcare and patient-level datasets
Strong understanding of Semantic Data Engineering principles
Experience building FAIR-compliant data pipelines
Experience with cloud-based data platforms and distributed processing frameworks
Strong Power BI development and data modelling skills
Ability to create reusable analytical datasets for dashboards and studies
Experience designing AI-ready datasets and analytics data products
Experience implementing automated data quality frameworks
Strong data profiling, validation, and monitoring skills
Understanding of healthcare data quality assessment methodologies
Excellent stakeholder management and communication skills
Ability to translate complex business requirements into technical solutions
Experience working with cross-functional global teams
Exposure to one or more of: Oncology, Respiratory, Immunology & Inflamation, Infectious Diseases

Benefits

Comp & perks

Equal opportunities employer
Inclusive and diverse working environment
B Corp accredited company focused on social and environmental performance, transparency, and accountability
AI-assisted recruitment with human-led assessments, selection decisions, and hiring outcomes