Azure Data Support Engineer
Location:
Newcastle or London preferred
Job Type:
Full-time | Permanent (On-Call Requirement)
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
.
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)
.