Jobs → Data & Analytics → Azure Data Engineer

About the Role We are looking for an Azure Data Engineer to design and build scalable data platforms for a US-based client. This role involves owning end-to-end pipelines on Azure, using Databricks, PySpark, and Azure Data Factory to transform raw data into reliable, analytics-ready assets. Key Responsibilities • Design, build, and optimize batch and streaming pipelines using Azure Databricks and PySpark. • Orchestrate ingestion and transformation workflows with Azure Data Factory (pipelines, triggers, linked services, parameterization). • Implement Medallion (Bronze/Silver/Gold) architecture on Delta Lake. • Tune Spark jobs for performance and cost (partitioning, caching, cluster sizing, Photon). • Build data models for reporting and analytics consumers (Power BI, Synapse, SQL). • Apply data quality checks, monitoring, logging, and error handling. • Implement governance and security with Unity Catalog, RBAC, and Key Vault. • Set up CI/CD for data pipelines using Azure DevOps or GitHub Actions. • Collaborate with client stakeholders, analysts, and architects to translate requirements into solutions. • Lead design reviews, mentor engineers, and drive best practices. Requirements • 4+ years in data engineering (7+ years for Senior). • Strong hands-on experience with Azure Databricks and PySpark. • Solid experience building production pipelines in Azure Data Factory. • Advanced SQL and Python. • Experience with Delta Lake, ADLS Gen2, and Azure data services. • Understanding of data warehousing concepts, dimensional modeling, and SCD handling. • Experience with Git and CI/CD practices. • Strong communication skills for working directly with US clients.