Software Development Engineer (Data Engineer)

Job Overview

Work on the HD Maps team at the forefront of geospatial big-data analytics and insights for customer market segments and product offerings. Expertise involves deploying GIS algorithmic stages into scalable production cloud applications using platforms like AWS and Spark, focusing on high-precision maps for ADAS, AV, and Non-Automotive GIS data customers. Responsibilities span data and systems analysis to automotive and cloud application architecture, including compute, storage, cost, and performance assessments.

Responsibilities

• 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 mapping products.
• Work closely with engineering teams to align product development with strategic objectives.
• Engage in direct communication with trend-setting customers and 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.

Qualifications

• Proficiency in Python or other programming languages commonly used in data analysis and cloud application development.
• Experience deploying GIS algorithms within scalable cloud applications, preferably on platforms 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

• 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.