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). We are looking for a versatile Azure Data & ML Support Engineer with strong expertise in Azure cloud services, Dev Ops, 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. Dev Ops & Automation Knowledge in maintaining CI/CD pipelines using Azure Dev Ops, Git Hub Actions, etc. for ADF, Databricks and ML models deployments.

Develop automation scripts using 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

Report troubleshooting

Support and maintain data warehouse environments, such as:

Azure Synapse Analytics SQL Server / Azure SQL DB Snowflake or Big Query (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 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 (e.g., Service Now, 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, Dev Ops, and automation

Opportunities to grow across data engineering, MLOps, and cloud automationA dynamic, learning-focused work environment with cutting-edge tools and processes