# Azure Data Engineer

> Weekday AI · Mumbai, India · Full-time · Posted 2026-09-17

**Salary:** INR 500,000–1,800,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

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.

## Requirements

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.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/B4B4E27B28/apply)

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