Technical Product & Automotive Data Specialist

Autofixer is a rapidly growing automotive e-commerce operating across multiple European markets. They handle millions of products and offers and develop automated solutions integrating product, vehicle, technical data, OE numbers, manufacturer catalogs, TecDoc/TecAlliance, and multiple external sources.

• Very good knowledge of the automotive parts market
• Experience with TecDoc/TecAlliance
• Understanding of TecDoc data structure and part-to-vehicle associations
• Understanding OE numbers, equivalents, applications, mounting criteria, and technical product data
• Understanding API operation and ability to read technical API documentation
• Familiarity with REST API, request/response models, endpoints, parameters, identifiers, and data structures transmitted
• Proficiency with data formats JSON, XML, CSV
• Understanding of database structures and data relationships
• Ability to analyze large datasets to identify errors or dependencies
• Ability to technically describe problems to developers
• Ability to independently locate data and data acquisition methods
• Understanding that solutions for millions of products require algorithms, rules, integration, or automation rather than manual work

Nice to have:

• Practical knowledge of SQL, basic Python, Postman, API tools, web scraping, Elasticsearch, PIM, or other systems managing large product catalogs
• Previous work experience with automotive parts manufacturers, distributors, large automotive e-commerce, or data providers using TecDoc/TecAlliance

• Working with TecAlliance/TecDoc data, manufacturer catalogs, and other automotive databases
• Analyzing data structures related to products, vehicles, applications, engines, technical parameters, and mounting criteria
• Developing product→vehicle→application→mounting condition linkages
• Analyzing OE numbers, equivalents, cross-references, and product relationships
• Acquiring and integrating data from multiple sources
• Working with REST API, feeds, and data formats including CSV, XML, and JSON
• Analyzing API documentation to determine usable data
• Testing API endpoints and analyzing data structures transferred
• Designing data mapping between external sources and internal catalog
• Analyzing identifiers, relationships, category structures, and data dictionaries across systems
• Extracting, cleaning, transforming, and merging large data sets
• Searching for new technical and product data sources
• Obtaining data from manufacturer websites and other services, including scraping when appropriate
• Creating rules to automatically classify, enrich, and correct data
• Detecting erroneous, missing, or ambiguous product–vehicle links
• Collaborating with developers on solutions for catalog, search, filtering, fitment, and recommendations