Posted 3mo ago

Azure Data Support Engineer

@ Avanade
London or Newcastle
OnsiteFull Time
Responsibilities:monitor pipelines, troubleshoot issues, develop automation
Requirements Summary:Azure, SQL, and data warehousing expertise; DevOps and automation skills; strong troubleshooting and communication abilities.
Technical Tools Mentioned:Azure Data Factory, Azure Databricks, Azure Machine Learning, Power BI Service, Azure DevOps, GitHub Actions, Python, PowerShell, Azure Monitor, Log Analytics, Application Insights, SQL Server, Azure SQL DB
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Job Description

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)

.