The Staff Data Engineer – Telematics Data Products joins a team focused on building next-generation telematics data products to power enterprise analytics, AI, and decision-making. You will design and build reusable, canonical data products and curated analytics-ready datasets that standardize metrics and business logic across engineering, product, and safety teams. Your daily work involves turning repeated analytical tasks into scalable solutions, improving performance and cost efficiency, and enabling self-service analytics. You will utilize Azure Databricks, SQL, Spark, and distributed data processing to manage complex telemetry, IoT, event-stream, and sensor data. The role solves the technical challenge of moving the organization from custom, duplicated logic toward trusted, reusable data products that provide insights into vehicle signals, battery health, and charging infrastructure.
What does a Data Engineer earn?
Median $159000 from 203 postings across 58 companies.
Design and build reusable telematics data products to support enterprise-wide analytics and AI.
Create canonical data products to simplify the joining and reuse of complex telemetry data.
Build curated, analytics-ready datasets that standardize metrics and business logic across teams.
Implement scalable data solutions using Azure Databricks to improve performance and cost efficiency.
Convert repeated analytical tasks into scalable, reusable data products to reduce duplicated effort.
Use data usage patterns and adoption signals to prioritize the data product roadmap.
Enable self-service analytics by improving data discoverability, trust, and consumption.
Develop data products specifically designed to support machine learning and advanced analytics use cases.
What we're looking for
Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field.
8+ years of experience in data engineering or analytics platforms, including senior or staff level experience with architecture and technical direction.
Deep hands-on experience with Databricks.
Strong skills in data modeling, semantic design, data architecture, SQL, Spark, and distributed data processing.
Experience designing solutions for performance, scalability, reliability, and cost optimization.
Experience working with IoT, telemetry, event-stream, or sensor data.
Experience enabling AI, machine learning, and advanced analytics through governed and reusable data products.
Master's degree in Computer Science, Data Engineering, Data Science, Analytics, or a related discipline (preferred).