Senior Data Engineer

90,000 - 100,000London AreaSenior Data EngineerWe're hiring a Senior Data Engineer to take technical ownership of a modern, AWS-native data platform, spanning everything from raw data ingestion and transformation to building scalable, reliable data pipelines that power production machine learning and AI systems.

This is a hands-on, high-autonomy role within a lean engineering team, where you'll work directly with senior technical leadership and have a genuine say in how the data architecture and platform evolve. The Engineering ChallengeYou'll own and evolve an AWS-native data environment, improving the reliability, scalability and performance of existing data infrastructure while building the foundations for future ML and AI initiatives.

The current stack includes:Data Engineering: Apache Iceberg, Kafka, Parquet and Amazon AthenaCloud Infrastructure: AWS-native data lake architecture, data ingestion, processing and storageArchitecture: AWS-based data lake (~5TB), with opportunities to modernise pipelines, optimise performance and improve platform maturityML & AI Integration: Supporting production ML workflows through SageMaker, with future opportunities around GenAI and LLM-powered diagnostic capabilitiesWhat You'll OwnDesigning, building and maintaining scalable, production-grade data pipelines across batch and streaming workloadsEvolving the AWS data lake architecture, improving data quality, reliability, performance and accessibilityBuilding and optimising data ingestion, transformation and processing workflows using modern data engineering technologiesWorking directly with data scientists, ML engineers and architects to ensure reliable, high-quality data is available for production ML systemsInfluencing architectural decisions, establishing engineering best practices and shaping the next generation of data infrastructureWhat We're Looking ForStrong hands-on experience building and operating production data engineering systemsDeep familiarity with AWS and cloud-native data architecturesStrong Python and SQL skills, with solid software engineering fundamentalsExperience designing and maintaining scalable ETL/ELT pipelines, data lakes or modern lakehouse architecturesUnderstanding of distributed data processing, streaming architectures and data pipeline optimisationSomeone who enjoys end-to-end ownership, technical problem-solving and working without layers of bureaucracyExperience with Apache Iceberg, Kafka, Parquet or Athena is highly desirable, while exposure to SageMaker or ML infrastructure is a bonus - production data engineering expertise is the priority.

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