Designs, builds, and maintains ETL/ELT pipelines, data warehouses, data models, and data quality processes. Integrates data from vendors and multiple sources, performs exploratory analysis to resolve data issues, and supports end-to-end data governance and operations. The role requires client interaction, mentoring junior engineers, and expertise in Python, PySpark, SQL, cloud platforms, Snowflake, Databricks, and pharmaceutical commercial data.
Roles & Responsibilities:
- Majorly responsible for designing, building and maintaining ETL/ELT pipelines.
- Integration of data from multiple sources or vendors to provide holistic insights from data.
- Build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms.
- Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in resolution.
- Client interaction experience required.
- Mentoring juniors and providing required guidance.
- Extensive hands-on experience in Python, Pyspark, SQL, Dataiku.
- Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
- Working knowledge in Databricks, Redshift, ADF etc.
- Hands-on experience in cloud services like Azure, AWS - S3, Glue, Lambda, CloudWatch, Athena.
- Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
- Familiar with SFDC, Waterfall/Agile methodology.
- Strong domain knowledge in Pharma domain/life sciences commercial data operations.
- Bachelor or Master Engineering/MCA or equivalent degree.
- 5-7 years of relevant industry experience as Data Engineer.
- Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
- High motivation, good work ethic, maturity, self-organized and personal initiative.
- Ability to work collaboratively and providing support to the team.
- Excellent written and verbal communication skills.
- Strong analytical and problem-solving skills.
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