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Data Analytics & AI AV
Austria
Wir suchen nicht nach einem AI Lead.
Wir suchen die Person, die das führende AI-Team Österreichs aufbaut.
Künstliche Intelligenz verändert gerade jede Branche, jedes Unternehmen und jede Rolle.
Die Frage ist nicht mehr, ob AI kommt.
Die Frage ist, wer die Zukunft gestaltet.
Genau dafür suchen wir dich.
Nicht als Teamleiter:in. Nicht als Projektmanager:in. Nicht als Verwalter:in.
Sondern als Unternehmer:in im Unternehmen.
Jemanden, der Menschen begeistert. Kunden inspiriert. Geschäft aufbaut. Talente anzieht. Und gemeinsam mit uns die AI-Erfolgsgeschichte von Avanade Österreich schreibt.
Was du bei uns bauen kannst
Du übernimmst nicht einfach ein Team.
Du gestaltest eine Bewegung.
Gemeinsam mit unseren Kunden, Microsoft, Accenture und internationalen AI-Expert:innen entwickelst du die nächste Generation von AI-Lösungen.
Dabei wirst du:
- Österreichs AI-Wachstum mitgestalten
- ein High-Performance-Team aufbauen
- Agentic AI, Copilots und moderne AI-Plattformen zum Einsatz bringen
- Kund:innen auf ihrer AI-Transformation begleiten
- Thought Leader am Markt werden
- unsere AI-Community prägen
auf Bühnen stehen und die AI-Diskussion in Österreich mitgestalten
Infrastructure AV
Australia
Summary
At the intersection of business transformation and Microsoft technology, we are looking for an Azure Cloud Architect who can help clients unlock value from their cloud investments.
In this role, you will lead from the front—combining deep Azure expertise, consulting mindset, and delivery excellence to design and implement enterprise-grade cloud solutions aligned with Microsoft’s Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF).
You will work closely with clients to shape cloud strategies, define architectures, and guide engineering teams through execution—delivering measurable business outcomes.
Key Responsibilities
Client Engagement & Consulting
Partner with enterprise clients to define cloud strategy, roadmap, and transformation initiatives
Translate business needs into scalable Azure solutions aligned to Microsoft best practices
Facilitate architecture workshops, design reviews, and executive-level discussions
Azure Architecture Leadership
Architect secure, scalable, and resilient Azure platforms across IaaS, PaaS, and cloud-native services
Design Azure Landing Zones aligned with Microsoft Cloud Adoption Framework (CAF) covering governance, security, and compliance
Guide teams on adopting modern cloud-native patterns (microservices, containers, serverless)
Microsoft Frameworks (CAF & WAF)
Lead cloud adoption journeys using CAF lifecycle (strategy → plan → ready → adopt → govern → manage)
Ensure solutions comply with Azure Well-Architected Framework principles (security, reliability, performance, and cost optimization)
Conduct architecture assessments and optimization reviews
DevOps & Automation Excellence
Drive DevOps culture adoption using Azure DevOps / GitHub Actions
Implement Infrastructure as Code (IaC) using Terraform
Build automated pipelines for continuous integration, deployment, and governance
Platform Engineering & Governance
Define enterprise-scale Azure governance models (RBAC, Policies, Management Groups)
Implement security and compliance frameworks using Microsoft-native tools
Establish monitoring, observability, and operational excellence practices
Delivery & Leadership
Lead and mentor cross-functional engineering teams
Ensure end-to-end solution delivery quality, scalability, and business alignment
Drive best practices, reusable assets, and accelerators
AI & Data
United Kingdom
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, 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
Data Analytics & AI AV
Brazil
Na Avanade, impulsionamos a inovação e habilitamos transformações digitais que realmente importam para nossos clientes. A posição de Consultor(a) Sênior Data Engineer (Snowflake) tem papel essencial na construção de soluções de dados modernas, escaláveis e seguras, apoiando projetos estratégicos e contribuindo diretamente para decisões mais inteligentes, operações otimizadas e experiências digitais avançadas. Esta pessoa será fundamental para fortalecer nossa capacidade analítica e acelerar a adoção de tecnologias de ponta no ecossistema de dados.
Buscamos alguém apaixonado(a) por desafios, inovação e excelência técnica, que queira fazer parte de um time colaborativo e orientado a impacto. Aqui, você terá oportunidade de crescer, evoluir sua carreira e contribuir com projetos que transformam negócios por meio de dados.
Together we do what matters.
Saiba mais sobre alguns dos nossos benefícios:
Vale refeição ou alimentação
Cartão Multibenefícios (até Consultor(a) Sênior)
Convênio médico e odontológico
Certificações e treinamentos
Seguro de vida
Previdência privada
Avababy: acompanhamento da gestação e kit para novos pais e mães
Participação nos resultados da empresa
Wellhub
Auxílio creche
Mentoria de carreira
Política de Birthday Off (para você e filhos até 12 anos)
Sessões de bem-estar
Para cargos gerenciais: veículo corporativo, estacionamento e auxílio combustível
Responsabilidades:
Projetar, desenvolver e manter pipelines de dados robustos, escaláveis e de alta performance.
Implementar e otimizar modelos e estruturas de dados na plataforma Snowflake, garantindo eficiência, governança e segurança.
Construir processos de ingestão, transformação e integração de dados usando ferramentas como DBT, Snowpipe, Embulk, Meltano ou similares.
Assegurar a qualidade dos dados por meio de testes, validações e monitoramento contínuo dos pipelines.
Otimizar consumo, armazenamento e performance no Snowflake (warehouses, clustering, caching, micro-particionamento, access control).
Apoiar iniciativas de arquitetura de dados e evolução da plataforma analítica.
Implementar métricas e processos eficazes de monitoramento e observabilidade.
Expor dados para usuários finais por meio de ferramentas como Power BI, Azure API Apps ou outras plataformas modernas de visualização.