Metyis is growing! At Metyis, we are looking for an Azure Data and Analytics DevOps Engineer with 5-8 years of experience, to join our Data and Analytics team at our Digital Campus in Porto.
We are Metyis, a forward-thinking, global company that develops and delivers solutions around Big Data, Digital Commerce, Marketing and Design and provides Advisory services. We have offices in 15 locations with a talent pool of 1000+ employees and more than 50 nationalities, dedicated to creating long-lasting impact and growth for our business partners and clients.
Together with HUGO BOSS, our esteemed business partner, we have embarked on a joint venture and created the HUGO BOSS Digital Campus, dedicated to increasing the data analytics, eCommerce and technology capabilities of the company and boosting digital sales. The HUGO BOSS Digital Campus employees will help create a state-of-the-art data architecture infrastructure, advanced business analytics, and the development and enhancement of HUGO BOSS’ eCommerce platform and services.
This collaborative environment will provide the capabilities required for HUGO BOSS to maximise data usage and support its growth trajectory towards becoming the leading premium tech-driven fashion platform worldwide.
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Develop your professional career working with one of the major brands in the fashion industry
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Opportunity to accelerate the pace of digitalization & eCommerce growth through advanced technology, business intelligence, and analytics
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Driving high-impact insights enhances decision-making across the entire organization
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Driving brand equity and digital sales through enhanced digital experiences
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Interaction with senior business and eCommerce leaders regularly to drive their business toward impactful change
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Become part of a fast-growing international and diverse team
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Strategic Leadership: Define and drive the DevOps strategy for the organization's Azure-based Data Platform, ensuring alignment with business goals and technological advancements.
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Architect and Optimize Pipelines: Design, develop, implement, automate, and continuously optimize advanced CI/CD/CT pipelines for complex data workflows, ensuring scalability, reliability, and efficiency.
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Big Data and Analytics Integration: Leverage Azure Data Services (e.g., Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure Data Lake) to integrate DevOps pipelines with big data workflows and frameworks like Apache Spark and Delta Lake.
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DevOps Governance: Establish and enforce DevOps best practices, including automated testing, deployment strategies, and compliance with security and regulatory standards.
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Advanced Cloud Security Practices: Implement Azure-native security features such as Azure Key Vault, Managed Identities, and Azure Policy to ensure secure infrastructure and data workflows.
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Incident Management and Optimization: Lead efforts in observability, monitoring, and incident resolution to ensure the platform's reliability and performance.
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Technology Evangelism: Stay at the forefront of emerging data technologies, trends, and best practices. Lead the evaluation and adoption of cutting-edge tools and methodologies to enhance the organization's DevOps ecosystem.
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Mentorship and Team Development: Mentor and coach data engineers, data scientists, and DevOps professionals, fostering a culture of technical excellence, collaboration, and continuous learning.
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Cross-Functional Collaboration: Act as a bridge between Data Engineering, Data Science, MLOps, and Cloud Infrastructure teams, driving seamless integration and alignment across functions.
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Extensive DevOps Expertise: 5+ years of hands-on experience as an Azure DevOps Engineer or in a similar senior role within Data & Analytics.
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Advanced Azure Knowledge: Deep expertise in Microsoft Azure services, with a focus on data platforms, security, and scalability.
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Mastery of CI/CD Tools: Extensive experience with CI/CD tools (e.g., Azure DevOps Pipelines, GitHub Actions) and the ability to design robust deployment pipelines. Hands-on experience integrating Databricks into CI/CD pipelines is a must.
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Big Data and Analytics Integration: Proven experience working with Azure Data Services and integrating DevOps pipelines with big data workflows and frameworks like Apache Spark and Delta Lake.
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Infrastructure as Code (IaC): Expertise in multi-cloud IaC using tools like Terraform and Azure Resource Manager (ARM) templates to ensure efficient and repeatable deployments.
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Proficient in Automation and Scripting: Advanced proficiency in scripting languages (e.g., Python, YAML, Git, Bash, PowerShell) to automate complex workflows. Experience with Python packaging and dependency management tools like Poetry to ensure efficient and reproducible workflows.
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Skilled in integrating Azure Data Factory into DevOps pipelines to orchestrate, automate, and streamline end-to-end data workflows with robust monitoring and deployment practices
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Testing and Quality Assurance: Strong experience in testing frameworks and data quality tools (e.g., pytest, Great Expectations) to ensure high standards of data reliability.
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Containerization and Orchestration: Advanced experience with containerization (e.g., Docker) and orchestration technologies (e.g., Kubernetes) for managing distributed systems.
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Advanced Cloud Security Practices: Expertise in implementing Azure-native security features such as Azure Key Vault, Managed Identities, and Azure Policy to ensure secure infrastructure and data workflows.
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Agile Leadership: Demonstrated experience working in and leading Agile environments (e.g., Scrum), driving team productivity and adaptability.
Nice to have:
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Azure Certifications: Advanced certifications such as Azure DevOps Engineer Expert, Azure Data Engineer Associate, Databricks Certified Data Engineer Associate, Azure Security Engineer Associate, and Terraform Associate (HashiCorp Certified).
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Version Control Leadership: Advanced proficiency in GitOps workflows and branching strategies (e.g., GitFlow, trunk-based development) for managing infrastructure and application code.
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Tooling and Ecosystem Knowledge: Experience with artifact management tools like Azure Artifacts to streamline dependencies and deployments.
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Software Engineering Expertise: Strong familiarity with software engineering best practices, including coding standards, design patterns, testing, and debugging.
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DataOps Mastery: In-depth knowledge of DataOps principles, including observability, monitoring, and incident reporting, to ensure operational excellence.
At Metyis, we are driven by curiosity and collaboration. We value diversity, equity, inclusion, and belonging (DEIB) in all its forms as it makes us stronger as an organisation and promotes creativity and innovation. We welcome all talents and are committed to creating a workplace where every employee can make a meaningful impact and grow.
