Azure Platform Operations Engineer

Azure Platform Operations Eng - AM- MFT KGS CH

The ADL / Databricks Platform Operations Engineer is responsible for providing business-as-usual (BAU) operational support for the Azure Data Lake (ADL) and Databricks platforms, with a primary focus on IST time zone coverage. This role is a key part of the U.S. ADL Platform Operations team and enables a support model to ensure platform availability, stability, and responsiveness.

• Provide operational support for Azure Data Lake and Databricks platforms during IST hours, ensuring continuity of support outside U.S. business hours.
• Maintain platform health across environments (DEV, QA, UAT, PROD); triage, investigate, and resolve operational issues or escalate as appropriate.
• Support BAU operational activities, including incident management, service requests, platform readiness checks, and ongoing operational maintenance.
• Act as a liaison between platform engineering, data engineering teams, and business stakeholders, ensuring alignment on operational priorities, support needs, and platform usage.
• Advise teams on ADL and Databricks operational best practices, including stability, performance, security, and efficient platform usage.
• Apply a high-level understanding of the full data stack (ingestion → storage → compute → orchestration → serving) to diagnose issues, assess downstream impact, and support reliable data delivery.
• Support and troubleshoot modern data hydration patterns, including incremental loads, CDC-based pipelines, backfills, and data freshness strategies, with an awareness of cost and performance tradeoffs.
• Monitor and improve platform observability through logging, metrics, alerting, and performance diagnostics; identify bottlenecks and proactively improve platform reliability.
• Ensure operational processes align with enterprise data quality, security, and governance standards.
• Identify recurring issues, operational gaps, and opportunities for process improvement or automation to enhance platform reliability and support efficiency.
• (Valuable but not mandatory) Contribute a system design mindset by considering scalability, reliability, and maintainability when evaluating operational issues or proposing improvements.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• Experience supporting Databricks or Azure-based data platforms in a production operations role.
• Hands-on experience with Azure services, including Azure Data Lake, Azure Data Factory, and/or Databricks.
• End-to-end cloud infrastructure understanding, with the ability to reason about how data platform components interact across the full data lifecycle.
• Experience with incident management, operational monitoring, and production support in an enterprise environment.
• Familiarity with industry best practices for data pipeline operations, including incremental processing, CDC, backfills, and data freshness management.
• Experience with system health monitoring, logging, alerting, and performance troubleshooting in distributed data platforms.
• Strong troubleshooting and analytical skills, with the ability to resolve complex operational issues.

Experience Level

Mid Level