AWS Data Engineer (Ref: 197894

Senior AWS Data Engineer - Ref197894

Nottingham (Hybrid) | 12-Month Fixed-Term Contract

Competitive Salary + Benefits

Contact - [email protected]

About The Company

Forsyth Barnes is partnering with a market-leading technology organisation currently investing heavily in a next-generation Analytics & AI platform.

As part of a major cloud transformation programme, our client is building a modern AWS-based data platform designed to power customer analytics, self-service reporting, APIs, machine learning and future AI products.

This is an opportunity to join a business where data is at the heart of product innovation and play a key role in shaping the future of its analytics capabilities.

The Role

We are looking for a Senior AWS Data Engineer to help design, build and optimise cloud-native data products and data pipelines within a modern AWS Lakehouse environment.

You'll work with large-scale operational and customer datasets, helping transform raw data into trusted, reusable products that support analytics, reporting and AI initiatives across the organisation.

This is a hands-on engineering role suited to someone who enjoys building scalable solutions, solving complex integration challenges and driving best practice across modern data platforms.

Key Responsibilities

• Design and develop scalable data pipelines and data products within AWS.
• Build and optimise lakehouse architectures supporting analytics and AI workloads.
• Develop transformations and reusable datasets using Python, SQL and dbt.
• Integrate data from multiple operational, API and third-party sources.
• Implement data quality, governance and lineage best practices.
• Collaborate with Product, Engineering and Analytics teams to deliver trusted data solutions.
• Support platform performance, reliability and cost optimisation initiatives.
• Contribute to the evolution of modern cloud data engineering standards and practices.

Requirements

• Strong commercial experience as a Data Engineer within AWS environments.
• Proven experience with services such as S3, Glue, Redshift, Athena or similar AWS analytics technologies.
• Excellent SQL and Python skills.
• Experience building ETL/ELT pipelines and cloud-based data solutions.
• Exposure to dbt, Spark or modern transformation frameworks.
• Understanding of data modelling, data quality and data governance principles.
• Experience delivering analytics, reporting or AI-ready data products.

Nice to Have

• Lakehouse architecture experience.
• Apache Iceberg experience.
• Terraform or Infrastructure as Code exposure.
• Experience in customer-facing analytics environments.

Package

• Competitive Salary
• 12-Month Fixed-Term Contract
• Hybrid working
• Private healthcare
• Enhanced holidays
• Professional development support
• Opportunity to work on a high-profile Analytics & AI transformation programme