• PUMA Group
  • 91074 Herzogenaurach, Germany
  • 03/04/2024
Full time Data Science Business Intelligence Statistics Data Governance

Job Description

SPEED & SPIRIT is what we look for in our candidates, defined by some simple values ​​that inspire us to BE DRIVEN in our performance, BE VIBRANT in our sporting legacy, BE TOGETHER in our team spirit, and BE YOU to let our individual talent and experience shine. Applying for a job at PUMA is easy. Simply click APPLY ONLINE and follow the steps to upload your application.


Data quality engineers need the following skills in order to be successful:

  • Data analysis: Data analysis is the process of evaluating data to determine its quality and usefulness. Data quality engineers use data analysis to determine what data is accurate and what data needs to be updated or removed. Data analysis requires attention to detail, logical reasoning and the ability to interpret data.
  • Database management: Database management is the ability to create and maintain databases. Data quality engineers often work with large amounts of data, so database management skills are essential. Data quality engineers may also work with data models, which are complex structures of data.
  • Communication: Data quality engineers often communicate with other members of a company's IT team, as well as with members of other departments. They may also communicate with clients and customers to explain data quality issues and solutions. Effective communication skills can help data quality engineers to convey information clearly and to build positive relationships with others.
  • Critical thinking: Critical thinking is the ability to analyze a situation and make a decision based on the information you have. Data quality engineers use critical thinking skills to determine the best methods for improving data quality. They may also use critical thinking to find solutions to data quality issues and to find ways to improve the data quality of large datasets.
  • Problem-solving: Data quality engineers use their problem-solving skills to identify and address issues that affect data quality. They may also use these skills to develop solutions to improve data quality. For example, a data quality engineer may use their problem-solving skills to identify and resolve issues with data that affects the accuracy of a company's marketing campaigns.

This opportunity will be available in full time or part time.


Data quality engineers are responsible for ensuring that the data used by our PUMA organization is accurate and consistent. They commonly work with a variety of different databases, applications, and other systems to ensure that all of this information is properly organized and easily accessible.

Data quality engineers may also be tasked with developing new methods or processes for improving the quality of data within the organization. This might include creating software tools or procedures for verifying the accuracy of incoming data or flagging issues that need to be addressed by data consumers.

Responsibility for Data Quality Platform

  • Develops standards for data quality and ensuring that these standards are followed throughout the organization
  • Evaluates the quality of data received from data sources to ensure that it meets company standards
  • Setups DQ Rules based on defined DQ guideline of data domain guidelines
  • Reaches out to Regional Domain Owner and Regional Data steward for data issues identified on data sent by regions
  • Creates data quality reports/dashboards for the different data domain owners to understand the quality of data being provided by their local IT
  • Enables DQ tool to regions and other potential departments who would find the platform useful to improve their data quality
  • Monitor quality of datasets (volume, distribution, freshness, schema)
  • Monitor the reliability of data pipelines
  • Automate data (quality) discovery, governance, and lineage tracing to build highly reliable, reusable data quality pipelines
  • Ensures all data related issues are addressed by respective functional area
  • Aware of all data related issues encountered and raised by the user
  • Go to person to check status of data issues
  • Review and analyze data to identify patterns or trends that may indicate errors or inconsistencies
  • Responsible for managing data structure changes (eg RBU/Business Segment remapping, …)

PUMA provides equal opportunities for all job applicants, regardless of race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, or disability. Equality for all is one of the core principles at PUMA and we do not tolerate any form of harassment or discrimination.

PUMA supports over 21,000 employees across 51 countries. The PUMA Group owns the brand PUMA, Cobra Golf and stichd, and is headquartered in Herzogenaurach, Germany.