Senior Software Development Engineer (Big Data), HD Maps

Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers. 

What We Do

On the HD Maps team, we are at the forefront of geospatial big-data analytics and insights for customer market segments and product offerings. Our expertise is pivotal in deploying GIS algorithmic stages into scalable production cloud applications, leveraging platforms like AWS and Spark. We work on Mapbox's award-winning high-precision maps (“HD Maps”) products family, spanning across ADAS, AV, and Non-Automotive GIS data customers in numerous projects. We cover everything from data and systems analysis to automotive and cloud application architecture, including compute, storage, cost and performance assessments.

What You'll Do

• Lead the initiation, design (requirements and specifications), and building of the product roadmap for algorithmic stages within cloud applications.

• Code and develop relevant algorithmic stages within cloud applications, utilizing technologies such as Python, SQL, AWS, and Spark, while ensuring high scalability.

• Collaborate across multiple R&D teams to seamlessly integrate analytics solutions into our mapping products.

• Work closely with engineering teams to align product development with strategic objectives.

• Engage in direct communication with trend-setting customers, automotive OEMs in EU, US, Japan, and China, as well as suppliers like automotive Tier 1 companies and Mapping firms.

• Collaborate with business development teams to ensure that the product roadmap and design align with customer needs and market trends.

What We Believe are Important Traits for This Role

• Bachelor's or Master's degree in Computer Science, Data Science, Geographic Information Systems (GIS), or a related field.

• Proficiency in Python or other programming languages commonly used in data analysis and cloud application development.

• Experience deploying algorithms within scalable cloud applications like AWS and Spark.

• Familiarity with data visualization libraries (e.g., Matplotlib, Plotly, D3.js) to effectively communicate insights.

• Strong problem-solving skills with meticulous attention to detail.

• Excellent communication skills and a proven ability to collaborate effectively across cross-functional teams.

Nice to Have Traits for This Role

• Prior experience in the mapping, navigation, or automotive industry.

• Understanding of geospatial data concepts and tools (GeoJSON, PostGIS, QGIS, etc.).

• Knowledge of machine learning techniques for geospatial data analysis.

• Contributions to open-source geospatial or data analysis projects.

What We Value

In addition to our core values, which are not unique to this position and are necessary for Mapbox leaders:

• We value high-performing creative individuals who dig into problems and opportunities.

• We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.

• We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.

• We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.

By applying for this position, you acknowledge that you agree to the Mapbox Privacy Policy which is linked here.

We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.

#LI-Remote