We are looking for a Data Engineer with 2–4 years of experience in building, maintaining, and optimizing data solutions on Microsoft platforms. The ideal candidate should have hands-on experience with Azure data services, SQL-based development, ETL/ELT pipelines, data warehousing concepts, and reporting integration. This role will work closely with data analysts, business teams, and application teams to deliver reliable, scalable, and secure data solutions. 

Key Responsibilities 

• Design, develop, and maintain data pipelines using Microsoft Azure data services such as Azure Data Factory Azure Data Lake, and Azure SQL Database. 

• Build ETL/ELT processes to ingest, transform, validate, and load data from multiple structured and semi-structured sources. 

• Develop and optimize SQL queries, stored procedures, views, and data models to support analytics and reporting needs. 

• Support data warehouse and data lake implementations, including data integration, data cleansing, and data quality checks. 

• Collaborate with business analysts, data analysts, and application teams to understand data requirements and deliver reusable data assets. 

• Monitor data pipelines, troubleshoot failures, and implement performance improvements. 

• Ensure data security, access controls, and compliance with organizational data governance standards. 

• Create and maintain technical documentation for data flows, source-to-target mappings, data models, and operational procedures. 

• Support Power BI datasets and reporting teams by preparing reliable and performance-optimized data layers. 

Required Technical Skills 

• Strong hands-on experience with SQL Server, T-SQL, stored procedures, functions, indexing, and query optimization. 

• Working knowledge of Azure Data Factory for pipeline development, orchestration, scheduling, and monitoring. 

• Experience with Azure SQL Database,  Azure Data Lake Storage, or related Microsoft data services. 

• Good understanding of ETL/ELT concepts, data warehousing, dimensional modeling, star schema, and incremental data loads. 

• Exposure to Power BI data preparation, semantic models, datasets, or reporting integration. 

• Basic to intermediate programming or scripting experience using Python, PySpark, or C# is preferred. 

• Understanding of data quality, metadata management, audit logging, and error handling in data pipelines. 

• Familiarity with Git, Azure DevOps, CI/CD concepts, and Agile delivery practices. 

Qualifications 

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline. 

• 2–4 years of relevant experience in data engineering, database development, ETL development, or data warehousing projects. 

• Hands-on experience working on Microsoft technology stack projects is required. 

• Ability to translate business requirements into technical data solutions. 

• Strong analytical, problem-solving, communication, and collaboration skills. 

Preferred Certifications 

• Microsoft Certified: Azure Data Engineer Associate. 

• Microsoft Certified: Azure Fundamentals. 

• Microsoft Certified: Power BI Data Analyst Associate. 

• Any SQL Server, data warehousing, or cloud data platform certification will be an added advantage. 

Selection Criteria 

• Demonstrated hands-on experience in building data pipelines using Azure Data Factory or equivalent Microsoft data tools. 

• Strong SQL development and troubleshooting skills, including ability to optimize queries and resolve data issues. 

• Practical understanding of data warehouse concepts, ETL design patterns, and data quality controls. 

• Ability to explain previous data engineering project experience clearly, including source systems, transformations, challenges, and outcomes. 

• Good communication skills and ability to work with cross-functional teams in an Agile environment. 

• Positive learning mindset with willingness to adapt to modern data platforms, automation, and AI-enabled data engineering practices.