Senior Data Engineer

In this Senior Data Engineer role you will own and evolve an AWS-native data platform, spanning from raw data ingestion to production-ready data pipelines for ML and AI systems. You’ll work in a lean engineering team with senior technical leadership and shape data architecture and platform maturity. You’ll tackle reliability, scalability and performance challenges to enable upcoming ML/AI initiatives. This role offers high autonomy and a clear impact on data quality and availability for production ML workloads.

• Design, build and maintain scalable production-grade data pipelines (batch and streaming)
• Evolve and optimise the AWS data lake architecture for reliability, performance and accessibility
• Ingest, transform and process data using modern data engineering technologies
• Collaborate with data scientists, ML engineers and architects to ensure high-quality data for production ML systems
• Influence architectural decisions and establish engineering best practices
• Enhance data quality, reliability and scalability of the data platform
• Support ongoing ML workflows through integration with SageMaker and related ML infra
• Drive end-to-end ownership of data infrastructure improvements

• Strong hands-on experience building and operating production data engineering systems
• Deep familiarity with AWS and cloud-native data architectures
• Strong Python and SQL skills with solid software engineering fundamentals
• Experience designing and maintaining scalable ETL/ELT pipelines, data lakes or modern lakehouse architectures
• Understanding of distributed data processing, streaming architectures and data pipeline optimisation
• End-to-end ownership, technical problem-solving and working without layers of bureaucracy
• Experience with Apache Iceberg, Kafka, Parquet or Athena is highly desirable; exposure to SageMaker is a bonus

• end-to-end ownership
• technical problem-solving
• collaboration with data scientists and ML engineers
• AWS
• Python
• SQL