Principal Data Engineer – RWE

This is a fully remote position, open to applicants in India.

📋 Description

• Design and implement data processes for the automated ongoing creation of patient-level data products for dashboards, reports, and research studies.

• Process datasets obtained from data vendors and partners, transforming them into usable formats for Real World Evidence (RWE) studies, dashboards, and other outputs.

• Convert diverse healthcare datasets into reusable data models suitable for observational research and epidemiological studies.

• Transform custom datasets into OMOP format as needed, while addressing any residual data that cannot be converted.

• Construct FAIR-compliant data pipelines and frameworks for semantic data engineering.

• Develop AI-ready datasets that facilitate generative AI applications.

• Collaborate with epidemiologists, statisticians, market access professionals, and health economists to identify requirements and convert them into actionable data structures.

• Work with the RWE programming team to establish data structures and support study outputs.

• Coordinate with IT to ensure that incoming datasets meet the specified requirements.

• Engage with technical personnel from analysis software vendors like Databricks.

• Maintain comprehensive documentation of data flows, schemas, pipelines, and processes.

• Design and execute data validation and monitoring to guarantee accuracy and reliability.

• Resolve issues related to data loading, extraction, and transformation.

• Collaborate with three other members of the Data Engineering team, providing support for workloads as necessary.

⛳️ Requirements

• Profound understanding of Real World Data (RWD) and Real World Evidence (RWE) concepts.

• Capability to evaluate business requirements and suggest suitable real-world healthcare datasets for analytical applications.

• In-depth knowledge of healthcare data models and ecosystems.

• Strong expertise in OMOP CDM versions 5.4 and 6, including extensions.

• Familiarity with SNOMED CT, RxNorm, ICD-10, LOINC, and HCPCS/CPT.

• Significant experience in constructing scalable ETL/ELT pipelines.

• Proficiency in Databricks, PySpark, Spark SQL, SQL, and Delta Lake.

• Experience handling large-scale healthcare and patient-level datasets.

• Strong grasp of Semantic Data Engineering principles.

• Experience creating FAIR-compliant data pipelines.

• Familiarity with cloud-based data platforms and distributed processing frameworks.

• Solid Power BI development and data modeling capabilities.

• Ability to develop reusable analytical datasets for dashboards and research studies.

• Experience in designing AI-ready datasets and analytics data products.

• Experience in implementing automated data quality frameworks.

• Strong skills in data profiling, validation, and monitoring.

• Knowledge of healthcare data quality assessment methodologies.

• Excellent stakeholder management and communication abilities.

• Proficient in translating complex business requirements into technical solutions.

• Experience working with cross-functional global teams.

• Exposure to one or more therapeutic areas including Oncology, Respiratory, Immunology & Inflammation, and Infectious Diseases.

🏝️ Benefits

• Equal opportunities employer.

• Inclusive and diverse working environment.

• B Corp accredited company committed to social and environmental performance, transparency, and accountability.

• AI-assisted recruitment featuring human-led assessments, selection decisions, and hiring outcomes.