Group Data Quality Engineer

🚀 We are looking for a Group Data Quality Engineer – Sales & Finance!

📍 Remote

Only candidates residing in Portugal will be considered

We are looking for an experienced professional to join the BI Platform Team, contributing to the reliability and continuous improvement of group-wide Sales and Finance Data Products. The role will play an important part in ensuring that business-critical data provides a solid foundation for transparent performance measurement and data-driven decision-making across the Group.

Responsibilities:

• Design, implement and continuously improve data quality controls covering completeness, accuracy, consistency, validity, timeliness and uniqueness.
• Translate business rules into measurable quality checks, automated tests, monitoring and alerting mechanisms.
• Develop and maintain data quality dashboards, scorecards, issue logs and service-level indicators.
• Analyse data anomalies, perform root-cause analysis and coordinate corrective actions with data owners and technical teams.
• Integrate automated quality checks into data pipelines and development processes to prevent defects from reaching reporting, analytics and AI use cases.
• Define and maintain critical data elements, validation standards, quality thresholds, ownership and escalation processes in line with the group data governance framework.
• Work closely with Sales and Finance stakeholders to address data quality challenges across customer, lead, revenue, parcel volume, pricing, cost, profitability and financial reporting processes.
• Contribute to shared engineering standards, documentation and reusable data quality components across the decentralised data platform.

Requirements:

• Bachelor's or Master's degree in Computer Science, Business Informatics, Data Engineering, Mathematics, Finance, Industrial Engineering or a related field.
• +5 years of experience in Data Quality, Data Engineering, Analytics Engineering or a similar data-focused role.
• Strong SQL skills and hands-on experience with data profiling, validation, reconciliation, root-cause analysis and automated testing.
• Experience with modern cloud data platforms and data pipelines, ideally Snowflake, including data modelling and transformation frameworks.
• Knowledge of data quality dimensions, monitoring approaches, metadata, data lineage and data governance principles, alongside an understanding of Sales and Finance processes.
• Experience with Python or other scripting/programming languages, version control, continuous integration and deployment practices.
• Ability to translate complex business requirements into clear, testable rules, communicate effectively with technical and business stakeholders, and drive issues to sustainable resolution.
• Practical experience leveraging AI tools for data profiling, quality analysis, anomaly detection, root-cause analysis, documentation and data engineering tasks.
• Very good English skills (B2 level required).