Azure Data Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟭𝟴𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟱-𝟭𝟴 𝗟𝗣𝗔)

Experience: 5+ yrs

Location: Mumbai, Maharashtra, India

Job Type: Full-time

We are looking for an experienced Azure Data Engineer with strong expertise in Microsoft Azure, Azure Data Factory (ADF), and SQL Server Integration Services (SSIS) to design, develop, and maintain scalable data integration and processing solutions.

The ideal candidate will have strong hands-on experience building data pipelines, integrating diverse data sources, transforming and processing large datasets, and supporting modern cloud-based data platforms. You will work closely with data analysts, architects, developers, business stakeholders, and other engineering teams to deliver reliable and high-quality data solutions.

The role requires a strong understanding of data engineering principles, ETL/ELT processes, cloud technologies, data integration, SQL, and production support.

Key Responsibilities

• Design, develop, and maintain scalable Azure data pipelines using Azure Data Factory.
• Build and manage ETL/ELT workflows for extracting, transforming, and loading data from multiple sources.
• Develop, enhance, and support SSIS packages for enterprise data integration.
• Create ADF pipelines, datasets, linked services, triggers, parameters, and integration workflows.
• Integrate data from SQL Server, databases, files, APIs, cloud applications, and other enterprise systems.
• Develop complex SQL queries, stored procedures, views, functions, and data transformation logic.
• Support migration of on-premise ETL workloads and SSIS processes to Azure-based data platforms.
• Implement incremental data loads, scheduling, dependency management, error handling, and retry mechanisms.
• Monitor production pipelines and proactively identify and resolve data integration failures.
• Troubleshoot performance, data quality, connectivity, and pipeline execution issues.
• Optimize ADF pipelines, SSIS packages, SQL queries, and data processing workloads.
• Implement data validation, reconciliation, and quality checks across data pipelines.
• Collaborate with Data Architects, BI Developers, Analysts, Software Engineers, and business stakeholders.
• Support deployment across development, testing, and production environments.
• Maintain technical documentation for pipelines, mappings, data flows, dependencies, and operational procedures.
• Follow data security, governance, access-control, and development standards.
• Use Git and modern CI/CD practices to manage data engineering code and deployments.
• Contribute to automation, process improvements, and modernization of existing data platforms.

What Makes You a Great Fit

• 5+ years of professional experience in data engineering, ETL development, data integration, or a related field.
• Strong hands-on expertise in Microsoft Azure, Azure Data Factory, and SSIS.
• Proven experience designing and developing complex ADF pipelines and ETL/ELT workflows.
• Strong experience with SSIS package development, deployment, troubleshooting, and optimization.
• Excellent knowledge of SQL Server and advanced SQL development.
• Experience with stored procedures, views, functions, joins, performance tuning, and query optimization.
• Strong understanding of data warehousing concepts, dimensional modelling, ETL architecture, and data integration patterns.
• Experience integrating data from relational databases, flat files, APIs, and cloud-based sources.
• Practical experience migrating or modernizing traditional ETL workloads to Azure.
• Familiarity with Azure services such as Azure SQL Database, Azure Blob Storage, ADLS, Synapse Analytics, or Databricks is an advantage.
• Experience with Git, CI/CD, Azure DevOps, and deployment automation is preferred.
• Strong troubleshooting, analytical, and problem-solving skills.
• Good understanding of data quality, security, governance, and production support practices.
• Strong communication and collaboration skills with technical and business stakeholders.
• Ability to manage multiple priorities and independently own data engineering deliverables.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline is preferred.