Backend Engineer

December 12, 2024

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PartsTech

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PartsTech is a platform that streamlines the process of ordering aftermarket parts and tires for automotive repair shops. The service connects users with over 225 parts and tire suppliers across more than 30,000 locations, enabling quick and efficient orders from a single system. PartsTech integrates with 35+ top shop management systems and allows for easy searching and ordering by part name, keyword, or through interactive diagrams. This tool is designed to save time, improve efficiency, and increase revenue for automotive businesses by optimizing their parts and tire sourcing operations.

Automotive Aftermarket • E-Commerce • Data Technology • User Experience • AutoTech

51 - 200 employees

🚗 Transport

☁️ SaaS

🤝 B2B

📋 Description

• PartsTech creates automotive e-commerce technology helping repair shops and auto part distributors run their businesses effectively • A backend software engineer for Search focused on the API, algorithms, and cloud backend • Develop and maintain the backend search engine and implement backend features like indexing and ranking algorithms • Collaborate with data scientists to experiment with and deploy ranking signals or personalization

🎯 Requirements

• Bachelor's Degree in Computer Science, Software Engineering • Advanced Degree (Master's or PhD) in Computer Science, Information Retrieval, Natural Language Processing, or Machine Learning is beneficial • Ideally proficient in Kotlin, JVM, Java Class Library for backend development • Other backend development experience such with as Node.js or Python will be considered • Familiarity with Go or Rust for high-performance requirements might be a plus • Strong experience with OpenSearch, ElasticSearch, and possibly Solr, or Algolia for indexing and retrieving search data • Familiarity with query optimization, indexing strategies, and search relevance tuning • Knowledge of vector search and embedding-based search for personalized or semantic search is beneficial • Proficiency with databases (both SQL and NoSQL), such as PostgreSQL, MySQL, MongoDB, or DynamoDB • Knowledge of caching solutions like Redis or Memcached to improve search response times • Understanding of data pipelines and ETL processes to ingest and process product or user data in near-real-time • Experience developing and implementing search algorithms for ranking, relevance scoring, and personalization • Knowledge of machine learning for search (e.g., natural language processing, embeddings) is advantageous, especially if working with personalized or semantic search features • Ability to design, develop, and optimize RESTful APIs or GraphQL for handling search requests and responses • Experience with microservices architecture and the ability to break down the search service into scalable, manageable components • Strong focus on performance and scalability to handle large numbers of search queries and rapid response times • Proficiency in monitoring tools (e.g., Prometheus, Grafana) and log analysis to identify performance bottlenecks • Understanding of API security best practices, such as authentication, rate-limiting, and data protection • Experience with distributed systems to ensure high availability and fault tolerance of the search engine • Proficient in Git for version control • Familiar with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) to automate testing and deployment pipelines