Data Quality Engineer

About Us

Planck Technologies is a company specialized in Software Development, dedicated to shaping futures and creating value through innovative IT solutions. By expanding teams and offering a comprehensive range of services from Software Development and Infrastructure Management to Cybersecurity we empower clients with all the expertise they need in one place. Inspired by the principles of quantum physics, we push beyond traditional boundaries to deliver customized solutions that redefine the IT landscape and drive shared success.

What are we looking for?

• Degree in Computer Science, Business Informatics, Data Engineering, Mathematics, Finance, Industrial Engineering, or a related field;
• Several years of proven 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;
• Knowledge of data quality dimensions, including completeness, accuracy, consistency, validity, timeliness, and uniqueness;
• Experience with data quality monitoring, automated controls, metadata, data lineage, and data governance principles;
• Understanding of data modelling and transformation frameworks;
• Experience with scripting or programming, preferably Python;
• Familiarity with version control, Continuous Integration (CI), and Continuous Deployment (CD) practices;
• Ability to translate complex business requirements and definitions into measurable, testable data quality rules;
• Understanding of Sales and Finance processes and data, including customer and lead management, revenue, pricing, costs, profitability, planning, and financial reporting;
• Strong analytical, problem-solving, and root-cause analysis skills, with great attention to detail;
• Ability to communicate data quality issues clearly to both technical and business stakeholders;
• Experience collaborating with international, cross-functional teams and driving issues through to sustainable resolution;
• Practical experience leveraging AI tools to support data profiling, quality analysis, anomaly detection, root-cause analysis, documentation, and data engineering tasks;
• Very good English skills (mandatory).

Nice to Have

• Experience working with Snowflake and modern data transformation frameworks;
• Knowledge of decentralised data architectures and group-wide data platforms;
• Experience building data quality dashboards, scorecards, monitoring solutions, and alerting mechanisms;
• German or another European language.

What will you do?

• Design, implement, and continuously improve group-wide data quality controls for Sales and Finance data products;
• Translate business rules and requirements into measurable data quality rules, automated tests, monitoring, and alerting mechanisms;
• Build and maintain data quality dashboards, scorecards, issue logs, and service-level indicators to provide transparent reporting across countries and business functions;
• Analyse data anomalies and recurring quality issues, perform root-cause analysis, and coordinate remediation with data owners, source-system teams, and data product teams;
• Embed automated data quality checks into data pipelines and development processes, ensuring that defects are identified early and do not reach downstream reports, analytics, or AI use cases;
• Define and maintain critical data elements, validation standards, quality thresholds, ownership, and escalation paths in line with the group data governance framework;
• Collaborate with Sales and Finance stakeholders to improve the reliability of customer, lead, revenue, parcel volume, pricing, cost, profitability, and financial reporting data;
• Contribute to shared engineering standards, documentation, and reusable data quality components across the decentralised group data platform;
• Leverage AI tools to support data profiling, anomaly detection, quality analysis, root-cause investigation, and the efficient delivery of data engineering tasks;
• Work closely with international business and technical teams to ensure consistent data quality standards and reliable group-wide data products.

Location: Lisbon

Working Model: Hybrid

We’re waiting for you! 🚀