Forsyth Barnes
AWS Data Engineer (Ref: 197894
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Senior AWS Data Engineer - Ref197894
Nottingham (Hybrid) | 12-Month Fixed-Term Contract
Competitive Salary + Benefits
Contact - callum.bell@forsythbarnes.com
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.
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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.
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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
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