Data Engineer
This is a Data Engineer role embedded within a cross-functional product squad, where data is treated as a product, not a service. You’ll work closely with Product Managers, engineers, and business stakeholders to shape how data supports customer experiences, decision-making, and growth.
Alongside building reliable, scalable data pipelines, you’ll help define metrics, translate product needs into data models, and ensure data is accessible, trusted, and actionable. This role is ideal for someone who enjoys combining technical depth with strong collaboration and a sense of ownership over outcomes.
We operate an Azure-focused technology stack, leveraging Azure Data Factory and SQL databases to build out data warehouse. To build the data warehouse to generate business value, you will collaborate with cross-functional squads and work closely with stakeholders to define data requirements, deliver solutions, and uphold best practices.
Key Responsibilities:
• Partner with Product Owners and stakeholders to translate business and product requirements into well-defined data models, pipelines, and metrics
• Design and develop scalable data pipelines, leveraging Azure Data Factory and other Azure-native tools.
• Own the data layer within your product area, ensuring data is reliable, well-modelled, and fit for decision-making and product use cases
• Collaborate with team members to optimize data architecture, ensuring high performance and reliability.
• Work with stakeholders to gather and refine data requirements, delivering solutions that align with business priorities.
• Implement and maintain version control practices (e.g., Git), facilitating collaboration and ensuring code quality.
• Maintain clear and comprehensive documentation of data workflows and processes.
• Coordinate task progress using Jira, tracking and prioritizing workload while working with cross-functional teams.
• Contribute to the development and enforcement of data engineering standards, best practices, and documentation processes.
• Actively participate in squad rituals (planning, refinement, retrospectives), contributing to prioritization and delivery decisions
• Assist in monitoring, troubleshooting, and improving data pipelines and ETL processes to support continuous improvement efforts.
• Stay up-to-date with industry trends and technologies to drive continuous improvement.
Requirements:
• Extensive experience as a Data Engineer with proven expertise in Azure data tools, particularly Azure Data Factory.
• Proficiency in SQL, Python, and data engineering frameworks.
• Solid understanding of data modelling (e.g. dimensional modelling, warehouse design, OLAP vs OLTP)
• Strong understanding of cloud platforms, preferably Azure, and familiarity with Azure-based data storage and processing solutions.
• Knowledge of data warehousing concepts, ETL/ELT practices, and data modelling techniques.
• Ability to solve complex data-related challenges and work independently on large data projects.
• Strong communication skills to work effectively with stakeholders and technical teams.
• Comfortable working within a cross-functional team and contributing to shared outcomes, not just individual deliverables
• Experience in financial services or banking data is advantageousю Experience working within an agile environment and product squad operating model