2 месяца назад
Azure Data Platform Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Azure Data Platform Engineer (Azure/Databricks): Designing and managing scalable cloud data platforms with an accent on migration strategy, infrastructure automation, and platform reliability. Focus on building robust CI/CD pipelines, implementing IaC with Terraform, and ensuring secure, high-performance data environments on Azure and Databricks.
Location: Must be based in the European Union region with a valid work permit
Company
A global AI-first digital transformation and engineering partner with over 25 years of experience, delivering data-driven solutions for enterprise clients.
What you will do
- Collaborate with architects and data engineers to design target-state data platform architectures.
- Manage cloud infrastructure using Terraform and IaC best practices.
- Deploy and maintain Kubernetes-based platform environments.
- Develop and maintain CI/CD pipelines for automated provisioning and operations.
- Implement security, governance, and identity management standards.
- Optimize platform reliability, scalability, and cost efficiency.
Requirements
- Must be based in the European Union region and hold a valid work permit.
- Strong hands-on experience with Microsoft Azure.
- Proficiency with Databricks and/or Microsoft Fabric.
- Extensive experience with Terraform and Infrastructure as Code.
- Hands-on experience with Kubernetes administration.
- Strong Python development skills for automation and tooling.
- Solid understanding of DevOps practices and CI/CD implementation.
Nice to have
- Experience with large-scale data platform modernization programs.
- Knowledge of dbt, Apache Airflow, or FinOps practices.
- Experience with observability, monitoring, and alerting platforms.
- Familiarity with data governance frameworks.
Culture & Benefits
- Focus on engineering excellence and continuous knowledge sharing.
- Consulting-oriented environment with exposure to diverse enterprise projects.
- Strong emphasis on professional growth and technical leadership.
- Collaborative culture working with global experts in AI and data.
Hiring process
- CV review
- HR call
- Technical interview
- Client interview
- Final decision
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