Senior Azure Data Engineer

Quick Facts

• Role: Senior Azure Data Engineer

Description

Design, build, test, and deploy scalable data pipelines for reporting and analytics use cases on Azure and Databricks. Own and improve production pipelines through refactoring and continuous operations, ensuring reliability, performance, maintainability, and observability. Collaborate with data and product stakeholders to deliver robust technical solutions, and lead incident diagnosis and durable corrective actions.

Responsibilities

• 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 new and existing pipelines to deliver data assets daily

• Translate reporting needs into technical solutions with Data professionals, Data Architects, Product Managers, and Engineering Managers

• Contribute hands-on to onboarding Core Products data workloads onto the Data Platform

• Ensure pipelines align with Data Platform 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

• Ensure clear documentation, monitoring, and operational ownership to support maintainability and reliable handover

• Share knowledge and engineering practices with the Core Products data team

Requirements

• 8+ years of professional experience in Data Engineering, including ownership of production-grade data pipelines

• Strong hands-on experience with Microsoft Azure and Databricks

• Advanced SQL and Python skills

• Experience designing, building, and operating data pipelines and analytical data products

• Knowledge of modern data-platform and lakehouse principles (e.g., medallion architecture, dimensional modelling)

• Experience with software engineering and DataOps practices (version control, automated testing, CI/CD, deployment, monitoring, incident management)

• Experience applying SRE practices and continuous operational improvements

• Strong stakeholder communication and ability to collaborate across Data, Architecture, Product, and Engineering teams

• Strong data modelling skills and ability to align scopes and business objectives before building

• Ability to work autonomously, make sound technical decisions, and document them clearly

Benefits

• Development budgets of up to 6,800 PLN

• Certifications funded (e.g., AWS, Azure)

• Access to Udemy and O’Reilly (formerly Safari Books Online)

• Events and technology conferences

• Technology Guilds, internal training, and Xebia Upskill

• Private medical healthcare

• MultiSport card subsidy

• Mental health support