About this Azure Data Engineer role at Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ญ๐ด๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฑ-๐ญ๐ด ๐๐ฃ๐)
Experience: 5+ yrs
Location: Mumbai, Maharashtra, India
Job Type: Full-time
We are looking for an experiencedย Azure Data Engineerย with strong expertise inย Microsoft Azure, Azure Data Factory (ADF), and SQL Server Integration Services (SSIS)ย 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.
Requirements
Key Responsibilities
- Design, develop, and maintain scalableย Azure data pipelinesย using Azure Data Factory.
- Build and manage ETL/ELT workflows for extracting, transforming, and loading data from multiple sources.
- Develop, enhance, and supportย SSIS packagesย 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 complexย 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 experienceย in data engineering, ETL development, data integration, or a related field.
- Strong hands-on expertise inย Microsoft Azure, Azure Data Factory, and SSIS.
- Proven experience designing and developing complexย ADF pipelines and ETL/ELT workflows.
- Strong experience withย SSIS package development, deployment, troubleshooting, and optimization.
- Excellent knowledge ofย SQL Server and advanced SQLย 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 toย 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 inย Computer Science, Information Technology, Engineering, or a related disciplineย is preferred.
