Principal Software Engineer, Data Engineering

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, Drive Well Fusion®, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior.

Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day.

CMT is looking for a Principal Software Engineer II, Data Engineering to help design the next generation of our data platform. You’ll build high-performance data systems that power analytics and machine learning, ensuring reliability, quality, and compliance  this role, you’ll lead architecture decisions, partner across teams, and drive best practices in data modeling, governance, and observability — all in support of CMT’s mission to make roads safer by making drivers better.

• Use independent judgment and discretion to lead the design and implementation of the company’s data platform and pipelines to support large-scale workloads, with a focus on data quality, observability, security, and compliance
• Define and champion best practices for data modeling, storage, governance, and ingestion and usage
• Develop, optimize, and maintain high-performance and reliable data pipelines and systems
• Partner with product, ML, and platform teams to evolve the company’s data ecosystem — ensuring scalability, reliability, and clear data ownership across domains
• Drive architectural decisions for the next generation of data platforms and ETL pipelines, balancing performance with governance and cost efficiency
• Lead data quality and lineage initiatives, advancing CMT’s data governance maturity and self-service data culture
• Identify opportunities to simplify and automate — improving data observability, testing, and deployment speed
• Influence upstream software design to ensure data capture aligns with analytical and ML needs.
• Mentor and train junior team members, fostering a culture of technical excellence and continuous improvement
• Provide support and troubleshoot production issues within data engineering systems and during business critical emergency scenarios
• Adhere to and improve established company development and operational standards and processes
• Complete any additional tasks as they arise

• Bachelor’s degree or equivalent years of experience and/or certification in Computer Science, Statistics, Mathematics, Electrical Engineering, or a related field
• 9+ years of experience in software or data engineering
• 4+ years of experience with cloud platform (AWS, Google Cloud Platform, Microsoft Azure)
• 4+ years of experience with data lake and warehouse solutions (AWS Redshift, Databricks or Snowflake)
• Proficiency in SQL and at least one of the following programming languages:
  Python, Java, or C++, with the ability for expanding knowledge
• Proven experience architecting and scaling production data systems handling billions of records or petabyte-scale workloads
• Deep understanding of data modeling, schema design, and performance optimization
• Experience with data orchestration tools (e.g. Airflow, Dagster, Prefect) and CI/CD practices in data pipelines
• Familiarity with data governance and metadata management tools (e.g. Amundsen, Data Hub)
• Demonstrated ability to drive data architecture and process improvements across multiple teams
• Strong communication skills with the ability to influence both technical and non-technical stakeholders

• Experience in mentoring technical teams and influencing architectural direction of upstream engineering teams
• Experience leading data mesh, data governance, or metadata management initiatives
• Background in streaming data pipelines (e.g. Kafka, Flink, Spark Structured Streaming)
• Familiari…