Senior Software Engineer, Data Engineering

Motional

11h•Hybrid

About The Position

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options. Mission Summary: The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year. The Senior Software Engineer, Data Engineering role is a high-impact position focused on building the scalable data infrastructure, developer tools, and cloud platform that underpins the organization's systems-level performance tracking. The mission of the team is to provide robust infrastructure and scalable tooling for producing, processing, and analyzing systems metrics at a massive scale, thereby accelerating the development of safe and reliable autonomous technology. The engineer will be responsible for creating essential components like CLI tools, web apps, cloud infrastructure, and SDKs for the metrics platform. Success in this role requires technical vision, an architectural mindset, and strong communication skills, as the Senior Software Engineer will act as a foundational pillar for the team, authoring design documents, driving engineering best practices, and architecting scalable solutions.

Requirements

5+ years of software engineering experience, with a strong focus on backend, data infrastructure, or platform engineering.
Deep expertise in Python, particularly in building scalable backend systems, SDKs, and CLI tools.
Proven experience working within AWS, data warehouses like Redshift, and open-source data formats like Iceberg and Parquet.
Experience working with DBT for data transformations and interacting with BI platforms like Looker.
Hands-on experience with Ray for scaling Python workloads.
Strong familiarity with containerization (Docker/Kubernetes) and setting up robust CI/CD pipelines via GitLab.
Demonstrated ability to write clear, concise, and thorough technical design documents and lead architecture reviews.

Nice To Haves

Prior experience working in data engineering pipelines for IoT / telemetry / sensors.
Experience working with autonomous vehicle data.

Responsibilities

Design & Architect: Author comprehensive technical design documents to propose, evaluate, and implement scalable infrastructure and tooling solutions.
Tooling & SDK Development: Build intuitive internal CLI tools, web applications, and Python-based SDKs leveraging Ray to streamline how engineers produce and interact with systems-level metrics.
Cloud Infrastructure: Architect, deploy, and maintain robust cloud infrastructure on AWS to support high-throughput data processing and analytics.
Data Pipeline Engineering: Leverage modern data tooling and formats (dbt, Apache Iceberg / Parquet, Redshift) to build highly efficient data pipelines, surfacing data effectively to BI platforms (Looker).
CI/CD & Containerization: Champion continuous integration and deployment best practices using GitLab, while deploying scalable services and workloads using containerization technologies.
Mentorship & Leadership: Act as a technical pillar on the team. Establish standards, mentor peers, and grow into a technical lead role guiding the future roadmap of our metrics infrastructure.

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