Data Engineer
Team: 474 COGS - Data Solutions
Location: Bengaluru, India
Commitment: F - Full Time
Workplace Type: hybrid
Responsibilities:
- Lead the design, development, and optimization of ETL/ELT pipelines using Databricks, Python, Spark, and Delta Lake.
- Architect scalable data solutions using Medallion architecture (Bronze, Silver, Gold layers).
- Design and implement data models and transformations using SQL and Python.
- Build and maintain audit frameworks to ensure traceability, compliance, and data lineage.
- Develop data quality monitoring and automated testing frameworks for pipeline reliability.
- Perform data analysis to support operational data requests and user queries.
- Collaborate with clinical data teams to analyse IRT/RTSM datasets.
- Create and maintain dashboards and reports using BI tools (e.g., Superset Power BI, Tableau, Qlik, or similar).
- Help manage CICD and automated code branching/deployment
- Ensure compliance with GxP, CDISC, and other regulatory standards.
- Mentor junior engineers and promote engineering best practices.
Experience
- 8–10 years of experience in data engineering, with leadership or team lead responsibilities.
- Strong hands-on experience with Databricks, Apache Spark, and Delta Lake.
- Advanced proficiency in SQL and Python for data transformation and automation.
- Experience with ETL/ELT orchestration, job optimization, and performance tuning.
- Proven experience designing and implementing audit, data quality, and testing frameworks.
- Hands-on experience with IRT/RTSM clinical trial data systems.
- Strong data analysis skills and ability to interpret complex datasets.
- Experience with BI/reporting tools such as Power BI, Tableau, or Qlik.
- Knowledge of clinical data standards (e.g., CDISC, SDTM, ADaM).
- Experience with cloud platforms (Azure, AWS, or GCP) and CI/CD pipelines.
Skills
- Experience in Pharma or Life Sciences, especially in clinical trial operations.
- Familiarity with data governance and metadata management tools.
- Certifications in Databricks, cloud platforms, or clinical data standards.
- Exposure to machine learning workflows or data science collaboration.
Education
- Bachelor’s degree in computer science, Engineering, or equivalent field or appropriate experience will be considered.
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