Data platform engineer

We are looking for a highly skilled and hands-on Data Platform Engineer to join our Data fabric team. In this role, you will design, build, and maintain secure, scalable, and reliable data pipelines that support enterprise analytics and data-driven decision-making.

Collaboration with analysts, application teams, and security functions is essential to deliver robust data solutions aligned with corporate standards, and security requirements.

You will apply DataOps best practices-including CI/CD, version control, automated testing, and documentation-while supporting production environments through monitoring, troubleshooting, and continuous improvement.

Key responsibilities :

• > Data pipeline design & engineering
• Design, build, and maintain secure, scalable, and reliable data pipelines supporting enterprise analytics and data-driven decision-making.
• Collaborate with analysts, application teams, and cloud, infrastructure, and security teams to translate requirements into robust technical solutions.
• Develop and manage data ingestion, transformation, and integration processes using the DDS-selected technology stack (MS Fabric, Azure, Terraform, some open source)
• Implement and maintain data models optimized for analytics, reporting, and downstream consumption.
• Apply engineering best practices including CI/CD, version control, automated testing, and documentation.
• Implement and maintain CI/CD for data workloads using GitHub integration and/or Azure DevOps pipelines.
• Use Infrastructure as Code (Terraform) for repeatable environment provisioning and controlled promotion across environments.
• > Platform reliability, quality & operations :
• Ensure data quality, consistency, availability, and performance across the data platform.
• Monitor, troubleshoot, and resolve issues in production data pipelines and platform components.
• Support operational activities such as incident management, performance tuning, and capacity planning.
• Contribute to continuous improvement of engineering standards and platform evolution
• > Enable and support internal data consumers :
• Provide onboarding, documentation, and best practices.
• Support analysts and application teams in using platform components.
• Contribute to governance (security, access models, data quality rules) .

Required qualifications and experience :

• Bachelor's degree in IT, Software engineering, Computer science, Business informatics, or equivalent relevant work experience.
• 5+ years of practical experience in a Data engineering role focused on production environments, including ETL/ELT, data warehousing, and data modeling.
• Strong experience with data engineering technologies, such as relational and non-relational databases, Microsoft Fabric, Microsoft Azure data services, open-source data technologies, Power BI.
• Strong proficiency in SQL ;
• Experience working with cloud-based data platforms and distributed data processing.
• Understanding of data security, access control, and governance principles in a corporate IT environment
• Familiarity with DevOps and DataOps practices, including CI/CD pipelines and GitHub, Azure DevOps, and Terraform-based IaC.
• Communication and collaboration : Ability to clearly document platform functionality and train/support engineering teams on tools, processes, practices.
• Fluency in English language : B2-C1 level for written and oral communication.
• Prior experience building a data platform or shared platform services for internal consumers.
• Ability to analyze complex data-related problems and deliver robust, maintainable solutions.
• Having relevant certificates ie Azure DevOps Engineer Expert, Azure Data Engineer Associate, MS Fabric Data Engineer Associate, etc.
• Autonomy and sense of ownership.
• Proactive problem-solving.
• Ability to work effectively with both technical and non-technical stakeholders.