Lead Analytics Engineer

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! We are looking for a highly skilled Lead Analytics Engineer to join our new Pricing Analytics Engineering team. As a part of the Pricing Domain, this team is responsible for creating and maintaining the pricing data models.

REQUIREMENTS:

• 2+ years in leading analytics engineering or data engineering teams
• 5+ years experience working in a Data Engineer role; e-commerce experience is a plus
• Experience working in a Data Warehouse environment creating and evolving dimensional data models to support analytics requirements
• Relevant experience with pricing data models would be preferred
• BA in Economics, Engineering, Mathematics, Computer Science, or another quantitative field
• Master’s degree or equivalent experience in Economics, Mathematics, or Computer Science preferred

HARD SKILLS:

• Experience building and maintaining data pipelines using ETL tools like SSIS, Talend or Airflow (would be preferred)
• Expert in SQL
• Experience working with cloud environments
• Familiarity with distributed column-store database management systems such as ClickHouse.
• Experience with big data technologies such as Hadoop, Spark, or Hive
• Experience working with a BI reporting tool like Tableau, Looker or Power BI
• Experience with CI/CD principles (version control, unit and automated tests)
• B2+ English

SOFT SKILLS

• Good analytical and problem solving skills
• Good understanding of the business processes of the e-commerce company
• Ability to find points of growth / possible areas of optimization in the company’s work and formulate action plans for implementing changes
• Commitment to continuous development, expansion of the range of professional skills, and automation of routine operations.

• Lead a small team of analytics engineers and lead the engineering strategy
• Create and evolve pricing data models to support self-service analytics needs
• Build scalable and robust data pipelines for the pricing data
• Work with various teams, inside and outside the domain, to create solutions that deal with large volumes of data and solve engineering problems
• Directly manage the relationship with Product and Business
• Track and monitor the data quality of the data models