data engineer for high-precision maps

Mapbox is a real-time location platform that provides tools for navigation and location-aware experiences. Organizations use its applications, data, SDKs, and APIs to power customized experiences for people, packages, and vehicles. The HD Maps team develops high-precision maps and scalable geospatial data analytics solutions for automotive and non-automotive GIS customers.

• Lead the initiation, design of requirements and specifications, and building of the product roadmap for algorithmic stages within cloud applications;
• Code and develop algorithmic stages within cloud applications using Python, SQL, AWS, and Spark while ensuring high scalability;
• Collaborate across multiple R&D teams to integrate analytics solutions into mapping products;
• Work with engineering teams to align product development with strategic objectives;
• Engage in direct communication with trend-setting customers.

• Expert knowledge of at least one programming language: Python, Scala, or Java;
• Strong software engineering fundamentals;
• Extensive experience designing and building large-scale data processing applications and pipelines on AWS or another cloud platform;
• Strong SQL skills, including query optimization, execution planning, and large-scale data processing;
• Deep understanding of distributed computing principles and hands-on experience with frameworks such as Spark;
• Experience designing and maintaining reliable data workflows using Airflow, Dagster, Prefect, or Luigi;
• Strong understanding of software architecture, design patterns, testing strategies, and CI/CD practices;
• Experience making architectural and technical decisions while balancing scalability, reliability, and maintainability;
• Strong analytical and problem-solving skills with the ability to drive complex technical initiatives;
• Excellent communication skills and experience collaborating across cross-functional teams;
• Fluent English, both written and spoken;
• Nice to have: Prior experience in the mapping, navigation, or automotive industry, knowledge of machine learning techniques for geospatial data analysis, contributions to open-source geospatial or data analysis projects.

• Supportive health care;
• Parental leave;
• Flexibility for personal circumstances;
• Teaching and learning environment;
• Commitment to a diverse and inclusive workplace.