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. Key Responsibilities: 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. Required Skills and Qualifications: 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) Preferred Qualifications: • 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 Work Hours & Availability: • Core business hours (08:30- 17:30) with rotational on-call support (1 in 4 weeks) • Flexibility for off-hours/weekend support during critical deployments or outages Why Join Us? • Be part of a high-impact team managing enterprise-scale Azure solutions • 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 Qualifications Required Skills and Qualifications: 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)