AWS Data Engineer (Ref: 197894

Forsyth Barnes

East Midlands

Hybrid

GBP 65,000 - 90,000

Full time

6 days ago
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Benefits offered by this job

Enhanced holidays

Job summary

Forsyth Barnes is partnering with a market-leading technology organisation to recruit a Senior AWS Data Engineer for a 12-month fixed-term contract in Nottingham (Hybrid). The role focuses on designing, building and optimising cloud-native data products and data pipelines in a modern AWS Lakehouse environment.

You will transform raw data into trusted, reusable datasets supporting analytics, reporting and AI initiatives, working across Product, Engineering and Analytics teams to deliver scalable,

Qualifications

  • Strong commercial experience as a Data Engineer in AWS environments.
  • Proven experience with AWS analytics services (S3, Glue, Redshift, Athena).
  • 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, quality and governance principles.
  • Experience delivering analytics or AI-ready data products.

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.

Skills

AWS
SQL
Python
ETL/ELT
dbt

Tools

S3
Glue
Redshift
Athena

Job 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.
Nice to Have
  • Lakehouse architecture experience.
  • Terraform or Infrastructure as Code exposure.
  • Experience in customer-facing analytics environments.
Package
  • 12-Month Fixed-Term Contract
  • Enhanced holidays
  • Opportunity to work on a high-profile Analytics & AI transformation programme
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