AWS Data Engineer (Ref: 197894
A senior data engineer designs, builds and optimises AWS cloud-native data pipelines and lakehouse data products powering analytics, reporting and AI for a technology company's transformation programme. Daily work centres on Python, SQL and dbt transformations, integrating operational, API and third-party data, with data quality, governance and cost optimisation on AWS.
- Compensation
- Not disclosed
- Location
- East Midlands, United Kingdom
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong commercial experience as a Data Engineer within AWS environments
- Proven experience with AWS services such as S3, Glue, Redshift, Athena or similar
- 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
- Terraform or Infrastructure as Code exposure
- Experience in customer-facing analytics environments
Full description
Nottingham (Hybrid) | 12-Month Fixed-Term Contract
Competitive Salary + Benefits
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.