At a Glance
- Tasks: Support and maintain Azure data solutions while troubleshooting and optimising performance.
- Company: Join a dynamic tech team focused on enterprise-scale Azure solutions.
- Benefits: Competitive salary, flexible hours, and opportunities for professional growth.
- Other info: Enjoy a learning-focused culture with cutting-edge tools and processes.
- Why this job: Work at the forefront of data, AI, and automation in a collaborative environment.
- Qualifications: Experience with Azure services, SQL, and strong troubleshooting skills required.
The predicted salary is between 45000 - 55000 £ per year.
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).
Key Responsibilities
- 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.
- DevOps & Automation: Maintain CI/CD pipelines using Azure DevOps, GitHub Actions, etc., for ADF, Databricks and ML model deployments. Develop automation scripts in 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, and report troubleshooting. Support and maintain data warehouse environments such as Azure Synapse Analytics, SQL Server / Azure SQL DB, Snowflake or BigQuery. 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.
Required Skills and Qualifications
- 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).
- DevOps & Automation: CI/CD using 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 such as ServiceNow and 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.
- Experience with AI Foundry, Gen‑AI, Fabric.
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.
Benefits
- 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.
Azure Data Support Engineer employer: 3004 Avanade UK Limited Company
Join a forward-thinking company as an Azure Data Support Engineer, where you will be part of a high-impact team dedicated to managing enterprise-scale Azure solutions. With a dynamic and learning-focused work environment in either Newcastle or London, you will have access to cutting-edge tools and processes, along with ample opportunities for professional growth in data engineering, MLOps, and cloud automation. Enjoy a supportive culture that values innovation and collaboration, making it an excellent place for those seeking meaningful and rewarding employment.
Contact Details:
3004 Avanade UK Limited Company Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Azure Data Support Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to Azure Data Support. Get comfy with explaining your past experiences and how they relate to the role – it’ll make you stand out!
✨Tip Number 3
Show off your skills! If you’ve got any projects or contributions to GitHub, make sure to highlight them. It’s a great way to demonstrate your hands-on experience with Azure services and scripting.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Azure Data Support Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Azure Data Support Engineer role. Highlight your experience with Azure services, SQL skills, and any relevant certifications. We want to see how your background fits with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your skills align with our needs. Don't forget to mention your experience with DevOps and automation – we love that stuff!
Show Off Your Problem-Solving Skills:In your application, give examples of how you've tackled challenges in previous roles, especially around troubleshooting and root cause analysis. We’re all about finding solutions, so let us know how you’ve done it before!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own channels!
How to prepare for a job interview at 3004 Avanade UK Limited Company
✨Know Your Azure Stuff
Make sure you brush up on your knowledge of Azure services, especially Azure Data Factory, Databricks, and Machine Learning. Be ready to discuss how you've used these tools in past projects, as well as any troubleshooting experiences you've had.
✨Show Off Your Scripting Skills
Since scripting is a big part of this role, be prepared to talk about your experience with Python and PowerShell. Maybe even bring along a sample script you've written that showcases your ability to automate tasks or solve problems.
✨Prepare for Real-World Scenarios
Expect questions that put you in the hot seat! Think about how you would handle job failures or performance issues in data pipelines. Practise articulating your thought process for root cause analysis and how you would implement solutions.
✨Communicate Clearly
Strong communication skills are key, especially when it comes to documentation and presenting your ideas. Practise explaining complex technical concepts in simple terms, as you might need to do this with clients or team members who aren't as tech-savvy.
