AWS Data Engineer (Ref: 197894)

Forsyth Barnes is partnering with a market-leading technology business undertaking a major Analytics & AI transformation programme.

As part of a strategic move from a large on-premise estate to a modern AWS-based analytics platform, our client is investing heavily in cloud-native data capabilities that will power enterprise reporting, customer analytics, AI initiatives and future data products.

This is an opportunity to join a high-impact programme and help shape the future of data architecture across the organisation.

We are looking for a Senior AWS Data Engineer to play a key role in designing, building and scaling a modern AWS data platform.

This is a hands-on engineering position requiring someone who has previously delivered cloud data platform initiatives and can combine technical leadership with practical delivery. You'll be responsible for helping move data from a large on-premise environment into AWS whilst establishing scalable ingestion frameworks, reusable data products and event-driven data capabilities.

The successful candidate will be comfortable mentoring engineers, challenging technical decisions and contributing directly to the build and ongoing evolution of the platform.

• Design, build and optimise AWS-native data pipelines and cloud data platform capabilities.

• Deliver ingestion solutions using CDC, event-driven and batch processing patterns.

• Build scalable ETL/ELT frameworks and reusable data products using Python and SQL.

• Support migration of data from a large on-premise estate into AWS.

• Design and implement robust data models supporting analytics and reporting requirements.

• Develop data quality, observability, governance and monitoring frameworks.

• Collaborate closely with Architects, Engineers, Data Scientists and Product teams.

• Provide technical leadership and mentoring whilst remaining hands-on.

• Support performance optimisation, cloud cost management and operational excellence initiatives.

• Proven commercial experience as an AWS Data Engineer or Data Platform Engineer.

• Strong experience working with AWS services including S3, Glue, Athena, EMR and Lambda.

• Advanced SQL and Python skills.

• Strong data modelling expertise, including dimensional modelling and analytics-ready data design.

• Experience delivering end-to-end cloud data platforms from ingestion through to consumption.

• Ability to lead and mentor engineers whilst remaining hands-on technically.

• Strong understanding of modern Data Engineering principles and best practices.

Desirable

• Change Data Capture (CDC) experience.

• AWS DMS experience.

• Event-driven architecture experience.

• Kafka and/or Flink.

• Apache Iceberg.

• dbt and Airflow.

• Lakehouse architectures and Medallion modelling.

• FinOps, observability and cost optimisation.

• Terraform and Infrastructure as Code.

• Meaningful ownership of cloud data engineering work that supports transportation, logistics and digitally enabled services.
• Technical scope across ingestion, lakehouse design, governance, data products and AWS platform optimisation rather than a narrowly defined pipeline remit.
• Exposure to analytics, machine learning and emerging AI initiatives as the organisation expands its data capabilities.
• Opportunity to influence reusable engineering standards, delivery patterns and the practical adoption of data-product principles.
• Collaboration with architecture, platform, software, product and analytical professionals across a varied technology landscape.
• Access to a role where strong engineering decisions can improve reliability, insight and operational performance at scale.
• Professional growth through hands-on work with modern AWS services, contemporary data practices and complex integration challenges.
• A competitive package aligned with the responsibilities and experience required for this position.

The position is based in Nottingham, England, and is suited to an engineer who combines strong AWS delivery skills with an interest in platform design and business outcomes. Experience from transportation, logistics, software, telecommunications or another data-intensive sector will transfer well.

Applicants should be prepared to demonstrate how they have improved the reliability, usability or governance of production data platforms. The successful candidate will bring curiosity, practical judgement and the ability to turn evolving requirements into robust engineering outcomes.