Azure Data Support Engineer

Azure Data Support Engineer

Location:

Newcastle or London preferred. Job Type: Full-time | Permanent (On-Call Requirement)

Security Clearance Requirement: This role is suitable for candidates who already hold UK Government Security Clearance (SC), or who are eligible and willing to undergo the SC vetting process (eligibility criteria apply).

• Azure Platform Support & Monitoring
  Support and maintain Azure-based data solutions, including Azure Data Factory pipelines, datasets, linked services, triggers;
  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.
• Dev Ops & Automation
  Maintain CI/CD pipelines using Azure Dev Ops, Git Hub Actions, etc., for ADF, Databricks and ML model deployments. Develop automation scripts in Python, Power Shell, 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, and report troubleshooting. Support and maintain data warehouse environments such as Azure Synapse Analytics, SQL Server / Azure SQL DB, Snowflake or Big Query. 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 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.

• Azure Services – Azure Data Factory (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).
• Dev Ops & Automation – CI/CD using Azure Dev Ops, Git Hub Actions, YAML pipelines.
• Scripting – Python, Power Shell.
• 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 such as Service Now and 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.
• Experience with AI Foundry, Gen‑AI, Fabric.

• Strong verbal and written communication.
• Good documentation and presentation skills.
• Ability to handle pressure and prioritize effectively in live support environments.

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.

• Be part of a high‑impact team managing enterprise‑scale Azure solutions.
• Work on the intersection of data, AI, Dev Ops, and automation.
• Opportunities to grow across data engineering, MLOps, and cloud automation.
• A dynamic, learning‑focused work environment with cutting‑edge tools and processes.