Group Data Quality Engineer Sales & Finance

emagine

Remoto
Introduction & Summary

We are seeking a Group Data Quality Engineer Sales & Finance to join our BI Platform Team. This role is pivotal in ensuring that sales and financial performance metrics are transparently measurable throughout the business lifecycle. The engineer will focus on implementing robust data quality controls and support data-driven decision-making processes within the organization.

Main Responsibilities

The core duty of this position includes designing and improving data quality controls for Sales and Finance data products.

  • Design, implement, and continuously improve data quality controls for Sales and Finance data products.
  • Translate business rules into measurable data quality rules and automated tests.
  • Build and maintain data quality dashboards and scorecards.
  • Analyze data anomalies and perform root cause analysis.
  • Embed automated data quality checks into data pipelines.
  • Define and maintain critical data elements and validation standards.
  • Partner with stakeholders to enhance data reliability.
  • Contribute to shared engineering standards and reusable components.

Key Requirements

  • Degree in computer science, business informatics, data engineering, mathematics, finance, or industrial engineering.
  • Several years of practical experience in data quality or data engineering roles.
  • Strong SQL skills with hands-on experience in data validation and automated testing.
  • Experience with cloud data platforms and data pipelines, ideally Snowflake.
  • Knowledge of data quality dimensions and data governance principles.
  • Understanding of Sales and Finance processes and associated data management.
  • Proficiency in scripting, preferably Python.
  • Strong analytical skills and attention to detail.
  • Ability to effectively communicate quality issues to business stakeholders.
  • Very good English skills; proficiency in German or other European languages is a plus.

Nice to Have

  • Experience with AI tools for data profiling and analysis.

Como aplicar?

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