Senior Azure Data Engineer (ID:3501)

As a Senior Azure Data Engineer, you will:

• Design, develop, and maintain scalable data pipelines and data processing solutions using Azure Databricks and Azure Data Factory.
• Build, optimize, and support ETL workflows to ensure reliable and timely data ingestion and transformation across enterprise data platforms.
• Manage run and operational activities, including monitoring data pipelines, identifying issues, and resolving incidents within defined SLAs.
• Ensure timely and accurate data onboarding from source systems into enterprise data environments.
• Develop and enhance data processing logic using Python, PySpark, and SQL to support large-scale analytics and reporting needs.
• Implement and manage workflow orchestration and scheduling using Apache Airflow.
• Support data governance and metadata management initiatives using the Atlas Framework.
• Troubleshoot and resolve complex data pipeline, performance, and data quality issues in production environments.
• Collaborate with cross-functional teams to ensure data availability, reliability, and operational stability.
• Create and maintain technical documentation, operational procedures, and best practices for data engineering processes.

What You Bring to the Table:

• 6–8 years of overall experience in data engineering and enterprise data platform environments, with a strong focus on cloud-based data solutions.
• Strong practical experience in building and managing data integration workflows using Azure Data Factory.
• Advanced proficiency in Python for data processing, automation, and pipeline development.
• Solid hands‑on experience with PySpark for large‑scale distributed data processing.
• Strong command of SQL for data querying, transformation, and performance optimization.
• Demonstrated experience in designing and supporting ETL pipelines in production environments.
• Practical experience using Apache Airflow for workflow orchestration and scheduling.
• Working knowledge of the Atlas Framework for data governance and metadata management.
• Experience supporting data platforms in run and operations mode, including incident management and SLA adherence.
• Strong analytical, troubleshooting, and problem‑solving skills.
• Effective communication skills and the ability to collaborate with cross‑functional technical teams.

You Should Possess the Ability to:

• Design and implement scalable, reliable, and high‑performance data engineering solutions on Azure.
• Automate and optimize data processing workflows using Python and PySpark.
• Proactively identify, analyze, and resolve data pipeline and performance issues.
• Manage operational responsibilities while ensuring data accuracy and timely data delivery.
• Work independently while taking ownership of end‑to‑end data engineering tasks.
• Collaborate effectively with technical and non‑technical stakeholders.
• Develop and maintain clear technical documentation and operational runbooks.

What We Bring to the Table:

• Opportunities to work on enterprise‑scale Azure data engineering initiatives.
• Exposure to modern cloud‑based data platforms and advanced data engineering technologies.
• A collaborative and professional environment focused on operational excellence and data reliability.
• Hands‑on experience with complex data ecosystems and enterprise‑level platforms.
• Continuous learning and professional growth opportunities in cloud data engineering.

Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.