Data Engineer, Data Quality & Provenance

Responsibilities

We are representing a confidential autonomous vehicle technology client seeking a Data Engineer focused on Data Quality & Provenance. In this role, you will build the data foundation that powers advanced AI development at petabyte scale. You'll transform vast volumes of fleet and simulation data into trusted, discoverable, and reproducible datasets that machine learning, autonomy, simulation, and safety teams rely on daily.

Your key responsibilities include:

• Design, build, and operate scalable batch and streaming pipelines for multimodal fleet and simulation data
• Create data models, catalogs, indexes, and query capabilities that make sensor, vehicle-state, map, and event data easy to discover and use
• Build versioned, reproducible datasets for training, evaluation, replay, scenario mining, and safety analysis
• Develop robust workflows for data ingestion, synchronisation, transformation, curation, labelling, and data-quality validation
• Partner with autonomy, ML, simulation, and safety engineers to define schemas, APIs, and data contracts
• Establish strong standards for lineage, observability, access controls, retention, and cost management across the data platform
• Improve the performance, reliability, and unit economics of large-scale storage and compute workloads

What We're Looking For

Essential qualifications:

• Strong hands-on Python and SQL skills, with solid production software-engineering fundamentals
• Experience designing and operating large-scale distributed data systems, beyond small-scale analytics or reporting pipelines
• Hands-on experience with distributed processing and workflow orchestration technologies, such as Spark, Flyte, Airflow, or equivalent tools
• Experience building and operating cloud-based data platforms using object storage, including data organisation, versioning, querying, governance, and cost management
• Proven ownership of data quality, lineage, observability, reproducibility, and incident response for production data workflows
• Experience translating ambiguous requirements from ML, data-science, robotics, or similarly technical teams into durable, reusable platform capabilities
• Comfort operating in ambiguity and helping define the boundaries, standards, and ways of working for a growing data platform

Desirable experience:

• Background in autonomous vehicles, ADAS, robotics, mapping, drones, or another sensor-rich domain
• Familiarity with time-synchronised sensor data, geospatial data, or multimodal datasets
• Understanding of ML training, evaluation, simulation, or closed-loop development workflows

This is a full-time, remote position. Our client operates a hybrid working policy that combines office collaboration with remote flexibility.

How We Work With You

Our talent team at Get A Job.ai partners with leading technology companies to connect exceptional candidates with confidential opportunities. When you apply through our platform, a dedicated recruiter will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client and guide you through each stage of their interview process. Please note that all applications must come through Get A Job.ai—direct contact with the client is not part of this process.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Get A Job.ai is an equal opportunity recruiter. We welcome and encourage applications from candidates of all backgrounds, experiences, and perspectives. We are committed to fostering an inclusive recruitment process that values diversity and ensures every candidate has an equitable opportunity to succeed.