Technical Lead-Data Engg Area(s) of responsibility Key Responsibilities • - Design and develop scalable ETL/ELT pipelines using PySpark, Spark SQL, Python, and Databricks.

- Develop complex transformation logic across Bronze, Silver, and Gold layers.
- Implement reusable transformation frameworks and common data processing utilities.
- Optimize transformation workloads for performance, scalability, and cost.
- Apply data quality, validation, and business-rule checks throughout the pipeline.
- Enterprise Data Modelling - Design scalable data models using:
- Dimensional modelling - Star/Snowflake schemas - Data Vault 2.0 - Canonical data models - Develop curated data products and analytical datasets using Databricks SQL and Delta Lake.
- Support enterprise-wide data harmonization across clinical, regulatory, safety, and commercial domains.
- Experience supporting data platforms across:
- Clinical trials – EDC, CDMS, CTMS - Regulatory and submission systems - Pharmacovigilance and safety - Commercial analytics - Real-World Evidence (RWE)



• Ensure adherence to relevant regulatory and data governance requirements including GxP, 21 CFR Part 11, HIPAA/GDPR, and ALCOA+ principles.

Required Qualifications • 10–15 years of experience in Data Engineering and enterprise data platforms.

- Strong hands-on experience with Databricks, Apache Spark, PySpark, Python, and SQL.
- 4+ years of experience with Databricks/Spark-based data engineering preferred.
- Solid experience in:
- Data migration and modernization • ETL/ELT development • Batch and streaming data pipelines • Delta Lake • Databricks Workflows • Unity Catalog • Data modelling • Data quality and reconciliation • Experience with cloud platforms – AWS/Azure/GCP.
- Strong understanding of CI/CD, Git, Jenkins, and DevOps practices.
- Experience working in Life Sciences/Pharma environments preferred.

Experience Level Senior Level

📌 Technical Lead - Data Engineering (Pune)
🏢 Birlasoft
📍 Pune