Azure Data Support Engineer

We are looking for a versatile Azure Data & ML Support Engineer with strong expertise in Azure cloud services, DevOps, SQL, and data warehousing to support and optimize ongoing operations in a Managed Services environment. This role is responsible for ensuring the stability, performance, and reliability of enterprise-scale data and machine learning workloads on Azure through proactive monitoring, issue investigation, automation, and continuous improvement., The ideal candidate will also play a key role in supporting data warehouse systems by managing SQL-based data loads orchestrated through Azure Data Factory (ADF), and by writing and optimizing SQL queries to aid in troubleshooting, data validation, and automation tasks., Azure Platform Support & Monitoring

• Support and maintain Azure-based data solutions, including:

• Azure Data Factory (ADF) pipelines, dataset, linked service, trigger
• Azure Databricks (Spark jobs, notebooks, clusters)
• Azure Machine Learning models and endpoints
• Power BI dashboards and dataset refreshes Monitor and troubleshoot failures in pipelines, jobs, and ML workflows using Azure Monitor, Log Analytics, and custom alerting.

DevOps & Automation

• Knowledge in maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, etc. for ADF, Databricks and ML models deployments.
• Develop automation scripts using Python, PowerShell, or Bash to reduce manual intervention and improve service reliability.

SQL and Data Warehouse Operations

• Write, optimize, and troubleshoot SQL queries for:

• Data validation
• Root cause analysis
• Report troubleshooting

• Support and maintain data warehouse environments , such as:

• Azure Synapse Analytics
• SQL Server / Azure SQL DB
• Snowflake or BigQuery (optional, if used in hybrid environments)

• Monitor ETL performance and investigate slow-running queries and data load failures.

Issue Investigation & RCA

• Investigate job failures and performance issues across data pipelines, ML endpoints, and dashboards.
• Perform root cause analysis (RCA) and provide short-term and long-term solutions.
• Develop and implement self-healing automation for recurring failures.

Service Operations & Support (Managed Services)

• Provide L2/L3 support aligned with ITIL practices (incident, problem, change management).
• Participate in on-call rotations and handle critical incident response.
• Maintain detailed SOPs, runbooks, knowledge base articles, and client documentation., * Work on the intersection of data, AI, DevOps, and automation
• Opportunities to grow across data engineering, MLOps, and cloud automation
• A dynamic, learning-focused work environment with cutting-edge tools and processes

Do you have experience in Spark?, * Azure Data Factory (ADF): pipelines, triggers, parameterization, monitoring

• Azure Databricks: Spark, notebooks, job orchestration
• Azure Machine Learning: pipelines, model deployment, monitoring
• Power BI Service: dataset refreshes, access control, report diagnostics

DevOps & Automation

• CI/CD: Azure DevOps, GitHub Actions, YAML pipelines
• Scripting: Python, PowerShell
• Monitoring: Azure Monitor, Log Analytics, Alerts, Application Insights

SQL & Data Warehousing

• SQL skills for debugging, data validation, and optimization
• Experience with Azure SQL DB, or SQL Server
• Familiarity with data modeling concepts and warehouse performance tuning

Support & Incident Management

• Strong troubleshooting and analytical skills for root cause analysisExposure to ITSM tools (e.g., ServiceNow, Jira) *, * Microsoft Certifications (e.g., DP-900, AZ-900, DP-203)

• Familiarity with AKS, Docker, or containerized ML environments

• Understanding of data governance and security in cloud environments

• AI Foundry, Gen AI, Fabric experience

Soft Skills:

• Strong verbal and written communication
• Good documentation and presentation skills
• Ability to handle pressure and prioritize effectively in live support environments, Azure Services
• Azure Data Factory (ADF): pipelines, triggers, parameterization, monitoring
• Azure Databricks: Spark, notebooks, job orchestration
• Azure Machine Learning: pipelines, model deployment, monitoring
• Power BI Service: dataset refreshes, access control, report diagnostics

DevOps & Automation

• CI/CD: Azure DevOps, GitHub Actions, YAML pipelines
• Scripting: Python, PowerShell
• Monitoring: Azure Monitor, Log Analytics, Alerts, Application Insights

SQL & Data Warehousing

• SQL skills for debugging, data validation, and optimization
• Experience with Azure SQL DB, or SQL Server
• Familiarity with data modeling concepts and warehouse performance tuning

Support & Incident Management

• Strong troubleshooting and analytical skills for root cause analysis

Exposure to ITSM tools (e.g., ServiceNow, Jira)

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