Data Engineer

• Design, develop, and optimize data pipelines in Azure Databricks using PySpark and SQL, applying Delta Lake and Unity Catalog best practices.
• Build modular, reusable libraries and utilities within Databricks to accelerate development and standardize workflows.
• Implement Medallion architecture (Bronze, Silver, Gold layers) for scalable, governed data zones.
• Integrate external data sources via REST APIs, SFTP file delivery, and SQL Server Managed Instance, implementing validation, logging, and schema enforcement.
• Utilize parameter-driven jobs and manage compute using Spark clusters and Databricks serverless.
• Collaborate with data analytics teams and business stakeholders to understand requirements and deliver analytics-ready datasets.
• Monitor and troubleshoot Azure Data Factory (ADF) pipelines (jobs, triggers, activities, data flows) to identify and resolve job failures and data issues.
• Automate deployments and manage code using Azure DevOps for CI/CD, version control, and environment management.
• Contribute to documentation, architectural design, and continuous improvement of data engineering best practices.
• Support the design and readiness of the data platform for AI and machine learning initiatives.

Data Engineer – Azure, Databricks

Senior Data Engineer

Senior Data Engineering Specialist

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer