Data Engineer Staff

Job Description Set the technical direction for Lytx's cloud data warehouse and lakehouse platform, balancing performance, cost, and reliability at scale. Design data models, pipelines, and storage layers that support analytics, reporting, and machine learning across the business. Partner with data engineering, analytics, product, and AI teams to translate business needs into platform capabilities. Lead complex, cross-team technical initiatives from design through delivery, and represent the data platform in architecture reviews. Improve data quality, governance, and observability so teams can trust the data they build on. Raise the bar on engineering practices through code review, design documents, and mentorship of engineers at all levels. Evaluate and introduce new tools and approaches where they solve a real problem, not for their own sake. Support the platform's ability to scale with Lytx's data volumes, including new data from AI safety features. What We're Looking For 10+ years of experience in data engineering, with a track record of designing and operating large-scale data warehouse or lakehouse platforms in production. Deep hands-on experience with a modern cloud data warehouse (e.g., Snowflake, BigQuery, or Redshift) and distributed data processing (e.g., Spark). Strong SQL and Python skills, and experience building and maintaining data transformation pipelines (e.g., dbt, Airflow, or similar orchestration tools). Solid understanding of data modeling, warehouse design patterns, and the tradeoffs between batch and streaming architectures. Experience operating data infrastructure on a major cloud provider (AWS, Azure, or GCP). A history of leading technical projects across teams and influencing architecture decisions without direct authority. Clear written and verbal communication you can explain a complex data model to both an engineer and a business stakeholder. A bias toward pragmatic solutions: you know when to build for scale and when to keep things simple. Nice to Have Experience with streaming data platforms (e.g., Kafka, Kinesis, or Flink). Experience supporting machine learning or AI feature pipelines. Background in IoT, telematics, video, or another high-volume sensor data domain. Experience with data governance, lineage, or cataloging tools. How We Work: DRIVE Lytx's culture runs on DRIVE: Deliver for the Customer, Responsibility in Every Outcome, Innovate with Purpose, Velocity with Excellence, and Elevate Each Other. As a Staff Engineer, you'll model these values daily — owning outcomes end-to-end, questioning assumptions to find better solutions, moving quickly without cutting corners, and investing in the growth of the engineers around you.