{"id":3060932,"url":"https://alion.io/job/avanade-azure-data-support-engineer","title":"Azure Data Support Engineer","company":{"id":712684,"name":"Avanade","domain":"avanade.com","url":"https://alion.io/company/avanade-3","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":106,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":13,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom","United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":173000,"period":"year","method":"role_country_seniority_unknown","sample_n":183},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Incident Management","optional":false},{"name":"ITIL","optional":false},{"name":"ITSM","optional":false},{"name":"Jira","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"Self-Healing","optional":false},{"name":"ServiceNow","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure AKS","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-09-02T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-23T03:59:49Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":52},"description":"Azure Data Support Engineer\nLocation:\nNewcastle or London preferred\nJob Type:\nFull-time | Permanent (On-Call Requirement)\nSecurity Clearance Requirement\nThis 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).\nWe 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.\nThe 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.\nKey Responsibilities:\nAzure Platform Support & Monitoring\nSupport and maintain Azure-based data solutions, including:Azure Data Factory (ADF) pipelines, dataset, linked service, trigger\nAzure Databricks (Spark jobs, notebooks, clusters)\nAzure Machine Learning models and endpoints\nPower BI dashboards and dataset refreshes\n\nMonitor and troubleshoot failures in pipelines, jobs, and ML workflows using Azure Monitor, Log Analytics, and custom alerting.\nDevOps & Automation\nKnowledge in maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, etc. for ADF, Databricks and ML models deployments.\nDevelop automation scripts using Python, PowerShell, or Bash to reduce manual intervention and improve service reliability.\nSQL and Data Warehouse Operations\nWrite, optimize, and troubleshoot SQL queries for:Data validation\nRoot cause analysis\nReport troubleshooting\n\nSupport and maintain data warehouse environments, such as:Azure Synapse Analytics\nSQL Server / Azure SQL DB\nSnowflake or BigQuery (optional, if used in hybrid environments)\n\nMonitor ETL performance and investigate slow-running queries and data load failures.\nIssue Investigation & RCA\nInvestigate job failures and performance issues across data pipelines, ML endpoints, and dashboards.\nPerform root cause analysis (RCA) and provide short-term and long-term solutions.\nDevelop and implement self-healing automation for recurring failures.\nService Operations & Support (Managed Services)\nProvide L2/L3 support aligned with ITIL practices (incident, problem, change management).\nParticipate in on-call rotations and handle critical incident response.\nMaintain detailed SOPs, runbooks, knowledge base articles, and client documentation.\nRequired Skills and Qualifications:\nAzure Services\nAzure Data Factory (ADF): pipelines, triggers, parameterization, monitoring\nAzure Databricks: Spark, notebooks, job orchestration\nAzure Machine Learning: pipelines, model deployment, monitoring\nPower BI Service: dataset refreshes, access control, report diagnostics\nDevOps & Automation\nCI/CD: Azure DevOps, GitHub Actions, YAML pipelines\nScripting: Python, PowerShell\nMonitoring: Azure Monitor, Log Analytics, Alerts, Application Insights\nSQL & Data Warehousing\nSQL skills for debugging, data validation, and optimization\nExperience with Azure SQL DB, or SQL Server\nFamiliarity with data modeling concepts and warehouse performance tuning\nSupport & Incident Management\nStrong troubleshooting and analytical skills for root cause analysis\nExposure to ITSM tools (e.g., ServiceNow, Jira)\nPreferred Qualifications:\nMicrosoft Certifications (e.g., DP-900, AZ-900, DP-203)\nFamiliarity with AKS, Docker, or containerized ML environments\nUnderstanding of data governance and security in cloud environments\nAI Foundry, Gen AI, Fabric experience\nSoft Skills:\nStrong verbal and written communication\nGood documentation and presentation skills\nAbility to handle pressure and prioritize effectively in live support environments\nWork Hours & Availability:\nCore business hours (08:30- 17:30) with rotational on-call support (1 in 4 weeks)\nFlexibility for off-hours/weekend support during critical deployments or outages\nWhy Join Us?\nBe part of a high-impact team managing enterprise-scale Azure solutions\nWork on the intersection of data, AI, DevOps, and automation\nOpportunities to grow across data engineering, MLOps, and cloud automation\nA dynamic, learning-focused work environment with cutting-edge tools and processes\n.\nRequired Skills and Qualifications:\nAzure Services\nAzure Data Factory (ADF): pipelines, triggers, parameterization, monitoring\nAzure Databricks: Spark, notebooks, job orchestration\nAzure Machine Learning: pipelines, model deployment, monitoring\nPower BI Service: dataset refreshes, access control, report diagnostics\nDevOps & Automation\nCI/CD: Azure DevOps, GitHub Actions, YAML pipelines\nScripting: Python, PowerShell\nMonitoring: Azure Monitor, Log Analytics, Alerts, Application Insights\nSQL & Data Warehousing\nSQL skills for debugging, data validation, and optimization\nExperience with Azure SQL DB, or SQL Server\nFamiliarity with data modeling concepts and warehouse performance tuning\nSupport & Incident Management\nStrong troubleshooting and analytical skills for root cause analysis\nExposure to ITSM tools (e.g., ServiceNow, 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