Data Scientist II
- Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF)
- Configure and manage Linked Services, Datasets, and Pipelines in ADF
- Develop and optimize data transformation workflows using Azure Databricks (PySpark)
- Work across Lakehouse architecture layers (Bronze/Silver/Gold), storage accounts, Unity Catalog, and support metadata‑driven design (control tables, mappings).
- Strong technical expertise across Power BI, SQL, Power Platform tools, and Azure services
- Build and manage dbt models for data transformation, testing, and documentation
- Implement real-time data ingestion using Azure Event Hub
- Integrate data from multiple sources (databases, APIs, cloud storage, on-prem systems)
- Ensure data quality by implementing dbt tests and validations
- Monitor, troubleshoot, and optimize data workflows
- Collaborate with cross-functional teams to understand business data requirements
- Maintain data governance, security, and performance standards
- Strong understanding of data warehousing concepts and ELT methodologies
- Experience working with Azure Data Lake Storage (ADLS) or similar storage solutions
- Knowledge of version control (Git) and CI/CD processes
- Willing to work in production support
- Configure and manage Linked Services, Datasets, and Pipelines in ADF
- Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF)
ALTEN
SopraSteria1
Zensar
ING Hubs
gxs
Perficient