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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and operating scalable data pipelines and platforms, with strong proficiency in Python and SQL. Capable of ensuring data quality, governance, and observability while collaborating with cross-functional teams in autonomous driving and machine learning.
Highest-signal resume keywords
Python ProgrammingSQL ProficiencyDistributed Data Systems DesignData Quality ManagementCloud-Based Data Platforms
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DesignData ModelingWorkflow OrchestrationData TransformationData GovernanceVersion ControlData QueryingData CurationData ValidationData Lineage
Soft Skills
CollaborationProblem-SolvingAdaptabilityCommunication
Tools & Technologies
SparkFlyteAirflowCloud StorageDistributed Compute Infrastructure
Industry Keywords
Autonomous VehiclesADASRoboticsGeospatial DataMultimodal Datasets
Tech Stack
Tools & technologiesAirflowCloudPythonSparkSQL
About the role
Key responsibilities & impact- Design and operate scalable batch and streaming pipelines for multimodal fleet and simulation data
- Build data models, catalogues, indexes and query capabilities for sensor, vehicle-state, map and event data
- Create versioned, reproducible datasets for training, evaluation, replay, scenario mining and safety analysis
- Develop workflows for data ingestion, synchronisation, transformation, curation, labelling and quality validation
- Partner with autonomy, ML, simulation and safety engineers to define schemas, APIs and data contracts
- Improve the reliability, performance and cost efficiency of large-scale storage and compute workloads
- Support autonomous-driving development across ML, autonomy, simulation and safety teams
- Develop metadata, geospatial and temporal indexing for data discovery, selection and scenario mining
- Combine real-world fleet logs with simulation and synthetic data for closed-loop development
- Establish data-quality standards, observability, access controls, retention policies and incident-response processes
- Work with cloud-based storage and distributed-compute infrastructure for reliability, scalability and cost efficiency
Requirements
What you’ll need- Strong hands-on Python and SQL skills, supported by solid production software-engineering fundamentals
- Experience designing and operating large-scale distributed data systems beyond small analytics or reporting pipelines
- Production experience with distributed-processing and workflow-orchestration technologies such as Spark, Flyte or Airflow
- Experience building cloud-based data platforms using object storage
- Understanding of data organisation, versioning, querying, governance and cost management
- Experience owning data quality, lineage, observability, reproducibility and incident response for production data workflows
- Ability to translate ambiguous requirements from ML, data-science, robotics or similarly technical teams into durable, reusable platform capabilities
- Comfort working in ambiguity and helping define standards and the operating model for a growing data platform
- Experience with autonomous vehicles, ADAS, robotics, mapping, sensor-rich systems, geospatial data or multimodal datasets would be an advantage
- Candidates may apply even if they do not meet every requirement
Benefits
Comp & perks- Salaries benchmarked against the market annually
- Meaningful equity, sharing in the ownership and long term success of Wayve
- Relocation support and visa sponsorship where applicable
- Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
- Learning and development budgets with support for training, conferences and growth
- Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more