Senior Azure Data Engineer

• At least 8 years of professional experience in Data Engineering, including ownership of production-grade data pipelines.
• Hands-on experience with Microsoft Azure and Databricks.
• Advanced SQL and Python skills.
• Experience designing, building, and operating data pipelines and analytical data products.
• Command of modern data-platform and lakehouse principles, including medallion architecture and dimensional modelling for reporting.
• Experience with software engineering and DataOps practices, including version control, automated testing, CI/CD, deployment, monitoring, and incident management.
• Experience with SRE practices and continuous operational improvements.
• Strong stakeholder communication skills and ability to collaborate across Data, Architecture, Product, and Engineering teams.
• Data modelling skills and ability to consider different data scopes and business objectives before making build decisions.
• Ability to work autonomously, make technical decisions, and document them clearly.

Nice to have:

• Experience with data governance, lineage, and access-control practices in Databricks, including Unity Catalog.
• Experience with payment or transaction data.
• Experience working in distributed international teams.

• Design, build, test, and deploy scalable data pipelines for reporting and analytics.
• Create production-ready pipelines for priority reporting use cases.
• Review and refactor existing reporting pipelines to improve reliability, performance, maintainability, and observability.
• Maintain pipelines so data assets are delivered reliably each day.
• Work with Data professionals, Data Architects, Product Managers, and Engineering Managers to translate reporting needs into technical solutions.
• Contribute hands-on to onboarding Core Products data workloads onto the Data Platform.
• Align pipelines with the Data Platform’s architecture, governance, security, and engineering standards.
• Ensure compliance with standards for data modelling, code quality, testing, CI/CD, documentation, security, and monitoring.
• Own SRE practices for data pipelines and products.
• Diagnose data incidents and pipeline failures, identify root causes, and implement corrective actions.
• Document data flows, dependencies, transformation logic, and operating procedures.
• Maintain documentation, monitoring, and operational ownership to support maintainability and handover.
• Share knowledge and engineering practices with the Core Products data team and contribute to its long-term autonomy.

• Recruitment process: CV review, HR call, interview, client interview, and decision.