Azure Data Support Engineer
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Occupation TypeIT business analysts, architects and systems designers
Occupation Code Skill LevelHigher Skilled
Sponsorship Salary Threshold
£54,900
(£28.15 per hour)
Occupation rate applies
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Description
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).
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
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).
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.
- 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
Azure Services
- 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.
- 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.
- 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 (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
- CI/CD: Azure DevOps, GitHub Actions, YAML pipelines
- Scripting: Python, PowerShell
- Monitoring: Azure Monitor, Log Analytics, Alerts, Application Insights
- SQL skills for debugging, data validation, and optimization
- Strong troubleshooting and analytical skills for root cause analysis
- Exposure 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
- 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, 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
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
- CI/CD: Azure DevOps, GitHub Actions, YAML pipelines
- Scripting: Python, PowerShell
- Monitoring: Azure Monitor, Log Analytics, Alerts, Application Insights
- 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
- Strong troubleshooting and analytical skills for root cause analysis