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Urgent! Trupti Solutions - Azure Data Engineer - ETL/SQL Job Opening In Pune – Now Hiring Trupti Solutions

Trupti Solutions Azure Data Engineer ETL/SQL



Job description

<p><p>We are seeking experienced Azure Data Engineers with 710 years of expertise in building and maintaining enterprise-grade data pipelines.<br/><br/> This role is ideal for senior professionals comfortable with modern cloud-based ecosystems and large-scale data handling.</p><br/><p><b>Overview : </b></p><br/><p>As an Azure Data Engineer, you will be responsible for designing, developing, and optimising data pipelines and ETL workflows across diverse data sources.<br/><br/> You will work closely with product, analytics, and QA teams to ensure the right data is available, clean, and optimised for business use cases.</p><br/><p><b>Experience Required : </b> 710 Years.</p><br/><p><b>Location : </b> Hybrid / Remote (Pune, Bangalore, Gurugram, Hyderabad).</p><br/><p><b>Key Responsibilities : </b></p><br/><p>- Build, optimise, and maintain scalable ETL/ELT pipelines on Azure.<br/><br/>- Design workflows leveraging Netezza, DataStage, DBT, and Snowflake.<br/><br/>- Collaborate with cross-functional teams to define data models and requirements.<br/><br/>- Perform SQL query tuning and ensure high data quality and reliability.<br/><br/>- Implement data governance, lineage, and security best practices.<br/><br/>- Support troubleshooting and production issues.</p><br/><p><b>Requirements : </b></p><br/><p>- 7 to 10 years of experience in data engineering.<br/><br/>- Strong hands-on experience with the Azure Data Engineering stack.<br/><br/>- Proficiency in Netezza, DataStage, DBT, Snowflake.<br/><br/>- Solid command over SQL and performance optimisation.<br/><br/>- Strong problem-solving skills and ability to work in hybrid/remote setups.</p><br/><p><b>Nice to Have : </b></p><br/><p>- Exposure to DevOps for Data (CI/CD for pipelines).<br/><br/>- Familiarity with Agile/Scrum delivery models.<br/><br/>- Experience in cloud cost optimisation.<br/><br/>- Prior exposure to data lake or big data ecosystems.</p><br/></p> (ref:hirist.tech)


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