Data Quality Analyst

at  AUTODOC

WHERE YOUR EXPERTISE IS NEEDED

AUTODOC is the largest and fastest growing auto parts ecommerce platform in Europe. Present across 27 countries with around 5,000 employees, AUTODOC generated revenue of over €1.3 billion in 2023, supplying more than 7.4 million active customers with its 5.8 million vehicle parts and accessories for car, truck, and motorcycle brands. Curious minds, adventurous experts and tech-savvy professionals - one team, one billion euros revenue. Catch the ride!

REQUIREMENTS

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Economics,
• Statistics, or a related field.
• Minimum of 3 years of experience in a data analytics or business intelligence role.
• Advanced proficiency in SQL for complex query writing and database management.
• Expertise in Power BI for developing reports, dashboards, and data visualizations.
• Strong programming skills in Python, especially with libraries related to data manipulation.
• Solid understanding of statistical concepts and experience in applying statistical methods to solve
• business problems.
• Proficiency in English at a B2 level or above to effectively articulate data-driven insights to
• non-technical stakeholders.
• Detail-oriented with strong analytical and problem-solving skills.
• Ability to work independently as well as part of a team in a fast-paced environment.

• Collaborate closely with business stakeholders to identify their data needs and define clear
• analytics objectives that support business goals.
• Design, develop, and maintain scalable analytics frameworks, leveraging SQL, Power BI, and
• Python to extract, transform, and analyze complex datasets.
• Create compelling, clear, and concise reports and dashboards using Power BI, ensuring that
• business users can easily understand and act upon the insights provided.
• Apply advanced statistical analysis to uncover trends, correlations, and patterns in data that can
• inform strategic business decisions.
• Provide ongoing support to business stakeholders, enabling them to leverage BI tools and
• insights effectively in their decision-making processes.
• Ensure the highest standards of data integrity and accuracy in all analytics outputs, implementing
• robust quality control and data validation processes.
• Conduct data validation and error-checking processes to guarantee the reliability and accuracy of
• analytics outputs, thereby upholding the trust in data-driven decision-making.