Informacje o stanowisku
To work successfully on projects you need:
- 3+ years of hands-on experience creating and maintaining data architectures, pipelines, and models
- Proven experience of working with Azure data services—e.g., Azure Synapse, Databricks, Data Factory, Azure SQL, Power BI—to deliver scalable, reliable solutions
- Proficiency with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automating deployments and infrastructure changes
- Familiarity with Agile methodologies (Scrum/Kanban) and ability to maintain clear documentation of processes, sprints, and user stories
- Basic understanding or exposure to Data Science techniques, including Generative AI concepts, ensuring data readiness for ML/AI workloads
- Strong communication skills to gather requirements from both technical and non-technical stakeholders and translate them into actionable data solutions
- Understanding of data governance principles (e.g., privacy, compliance) and security best practices on Azure
- Ability to monitor and optimize performance of ETL/ELT jobs, storage layers, and analytics workloads
- At least B1+ level of English
Will be a plus:
- Experience building or maintaining enterprise-grade data platforms, including cross-cloud integrations
- Microsoft Certifications (e.g., Azure Data Engineer Associate) or other relevant credentials
- Experience with Terraform, Bicep, or ARM for infrastructure-as-code
- Familiarity with containerization and orchestration (Docker, Kubernetes)
- Knowledge of metadata management and data cataloging tools (e.g., Purview, Collibra)
- Familiarity with modern AI tools and practical experience applying them to security operations
Requirements: Python, Azure, CI/CD, Agile, Data science, AI, Data governance, ETL, Terraform, Bicep, Docker, Kubernetes
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