Software Engineer II - Data Platform

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone. When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif. Meet the team: As Latitude’s Data Platform team, our mission is to build the scalable, high-performance infrastructure that turns structured data into insight to drive Latitude’s business forward. We provide foundational solutions for handling, processing and visualizing large-scale data to ensure every team at Latitude—from Autonomy to Machine Learning to Fleet Operations—can measure what matters. We promote Data as a Product ; this means applying rigorous software engineering discipline to data assets: versioning, public/private interfaces for data models, and a relentless focus on automated testing. To scale these principles across our org, we design self-service systems that prioritize continuous, iterative delivery, developer velocity, cost transparency and efficiency by default. What you’ll do: In this role, you will help build and evolve: A High-Performance Cloud-Native Stack : Work with a blend of serverless cloud analytics tools and self-hosted Kubernetes deployments to serve a diverse range of internal stakeholders Abstracted Data Frameworks : Develop internal tooling that enables engineers to self-serve data loading and testing. You’ll work on systems capable of handling high-throughput, low-latency streaming and massively parallel bulk loads scaling to hundreds of terabytes daily, with robust support for generic and customer-defined data unit and integration testing and monitoring. You’ll work closely with teams such as Latitude’s Autonomy Analytics team, among many others, to understand and generalize platform feature needs and provide guidance/documentation on usage Open Source Custom Tooling : We deploy and scale industry-leading data engineering and analytics tools. We lean into the open-source ecosystem, deploying and extending OS solutions such as dbt, Airflow and Superset to serve Latitude’s unique autonomy and ML use cases A Rich Metadata Layer : Provide the automation and cataloging tools that serve as the backbone for discovery and tracing. You will play a key role in enabling a well-documented data front ready for both human exploration and LLM/RAG-based consumption What you'll need to succeed: Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 2+ years of relevant experience, Master's degree, or PhD Software Craftsmanship : Strong Python development skills with a focus on SOLID design principles. You have experience managing the full lifecycle of internal packages, from intake and design to release and maintenance. Cloud Infrastructure : Experience managing cloud infrastructure via Infrastructure as Code (IaC). You should be comfortable with Docker, Terraform, Kubernetes, Helm, and observability via Grafana or similar. Data Fluency : Understanding of SQL and OLAP concepts. You are familiar with the architecture of Massively Parallel Processing (MPP) systems (e.g., BigQuery, Redshift, or ClickHouse) and understand how to optimize for both performance and cost. Experience with dbt is a plus. Distributed Orchestration and Streaming : Familiarity with data orchestration tools (e.g., Airflow, Dagster) and a conceptual understanding o ... (truncated, view full listing at source)