> Markdown version of [/jobs/ext/4663726-senior-software-engineer-data-and-orchestration](https://www.wearedevelopers.com/jobs/ext/4663726-senior-software-engineer-data-and-orchestration). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Data and Orchestration - **Company:** Wayve - **Location:** London, United Kingdom (Remote available) - **Experience:** Expert - **Salary:** £95,487 - **Contract:** Permanent contract - **Skills:** Airflow, Batch Processing, Big Data, Databases, Information Engineering, Data Warehousing, Relational Databases, Programming Tools, Distributed Computing Environment, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, Performance Tuning, Workflow Management Systems, Data Processing, Data Ingestion, Apache Spark, Kubernetes, Apache Kafka, Vertica, Data Pipelines - **Published:** November 11, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5961481849 ## About the Role + Strong software engineering fundamentals and solid Python programming skills, with experience designing, building and maintaining production-grade systems + Experience building or operating DAG-based workflow orchestration and data pipeline systems, using tools such as Airflow, Dagster or Flyte. + Experience with distributed computing frameworks such as Ray or Spark + Experience working with systems at scale, ideally involving distributed systems, large data volumes or high-throughput processing + Experience deploying and operating production workloads on Kubernetes, including troubleshooting issues and managing resources for reliable, scalable data-processing services. + Familiarity with distributed event streaming platforms such as Apache Kafka + Strong understanding of database principles and consistency models-including eventual and strong consistency in distributed systems-with practical familiarity with relational databases and data warehouses such as Postgres and ClickHouse + Strong collaboration skills, with the ability to work closely with platform users and partner teams to translate requirements into scalable technical solutions Desirable + Experience with machine learning infrastructure, inference systems or ML performance optimisation + Exposure to large-scale batch processing, compute scheduling or resource prioritisation + Experience building shared libraries, developer tooling or internal platforms used across multiple teams Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement. ## Description The Data and Orchestration team in London builds the platforms behind Wayve's data engineering, orchestration and inference workflows. Our infrastructure lets partner teams ingest, process and transform high-volume data from external vendors, vehicle fleets and customer programmes, and we make sure those systems are reliable, efficient and easy to use. Your day-to-day You'll help evolve Wayve's data pipeline platform. That means revamping our existing Harness system and building a new DAG-based orchestration system for our fleet's next-generation data volumes. You'll work on infrastructure used across the company, supporting high-priority data runs, batch inference, evaluations and business-critical incident response, and you'll work closely with partner teams to understand what they need from their pipelines. What you'll be working on * Designing, building and evolving scalable data pipeline and orchestration infrastructure for Wayve's next-generation autonomous driving data platform * Revamping the existing Harness system and developing a new DAG-based workflow platform * Building tooling and libraries that make data ingestion, processing, inference and evaluation workflows simple, reliable and consistent across teams * Making sure the platform runs hundreds of parallel pipeline steps efficiently, with correct outputs, no conflicts and effective resource prioritisation * Supporting batch inference and performance optimisation workflows, so teams can run evaluations in a cost-effective and scalable way * Improving platform reliability, quality and usability, including incident response workflows aligned to business-defined SLOs