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Group Data Quality Engineer

Remote

Job description

We are looking for a Group Data Quality Engineer – Sales & Finance for a fully remote position.

About the Role

You will join a BI Platform Team that builds the foundation for data-driven decisions across an international group. With a modern decentralised data architecture and platform services, from raw data and self-service to machine learning and visual analytics, the team enables business departments to use data efficiently, flexibly and responsibly.

You will contribute to the development of group-wide Sales & Finance Data Products, with the goal of making sales and financial performance transparently measurable across the full business lifecycle: from leads and opportunities to new customers, volumes, pricing, revenue, costs, profitability and financial reporting.

You bring strong analytical problem-solving skills, attention to detail and a structured, proactive and independent working style. You are confident collaborating across business functions, countries and technical teams, communicate quality issues in a business-oriented way, and drive issues to sustainable resolution.

Main Responsibilities

  • Design, implement and continuously improve group-wide data quality controls for Sales and Finance data products, covering completeness, accuracy, consistency, validity, timeliness and uniqueness.
  • Translate business rules and requirements into measurable data quality rules, automated tests, monitoring and alerting.
  • Build and maintain data quality dashboards, scorecards, issue logs and service-level indicators that provide transparent reporting across countries and business functions.
  • Analyse data anomalies and recurring quality issues, perform root-cause analysis and coordinate sustainable remediation with data owners, source-system teams and data product teams.
  • Embed automated data quality checks into data pipelines and development processes, so defects are identified early and prevented from reaching 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.
  • Partner with Sales and Finance stakeholders to improve the reliability of customer, lead, revenue, 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.


Requirements

  • Degree in computer science, business informatics, data engineering, mathematics, finance, industrial engineering or a comparable field.
  • Several years of practical experience in data quality, data engineering, analytics engineering or a comparable 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, controls, monitoring approaches, metadata, lineage and data governance principles.
  • Understanding of Sales and Finance processes and data, such as customer and lead management, revenue, pricing, costs, profitability, planning and financial reporting.
  • Experience with scripting or programming, preferably Python, and with version control, continuous integration and deployment practices.
  • Ability to convert complex business definitions into clear, testable rules.
  • Practical experience leveraging AI tools to support data profiling, quality analysis, anomaly detection, root-cause analysis, documentation and efficient delivery of data engineering tasks.
  • Very good English skills.

Nice to Have
German or another European language.


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