AWS Data Engineer

Harnham - Data & Analytics Recruitment
Manchester, United Kingdom
Today
£80,000 – £90,000 pa

Salary

£80,000 – £90,000 pa

Job Type
Permanent
Work Location
Hybrid
Seniority
Mid
Education
Degree
Posted
30 Apr 2026 (Today)

Data Engineer

Manchester (2x week in office)

£80,000 to £90,000

This is an opportunity to join a scaling SaaS business where data sits at the heart of the product. You will play a key role in shaping modern data infrastructure that directly supports machine learning systems, real time decision making, and measurable commercial outcomes. The role offers high ownership, greenfield projects, and the chance to influence how data is used across the organisation as it continues to grow.

The Company

They are a UK based technology scale up building a privacy first, cookieless platform that helps businesses protect and optimise their digital marketing spend. Using machine learning and large scale behavioural data, they analyse vast volumes of traffic in real time to identify low quality or invalid activity. With offices in London and Manchester, they operate at Series A stage with strong funding and a collaborative, engineering led culture.

The Role

You will sit within the Data and Platform function, working closely with Data Science, Engineering, and Product teams to design and run reliable, scalable data systems. Key responsibilities include:

  • Designing and owning batch and streaming data ingestion pipelines on AWS
  • Building and maintaining ML ready datasets to support model training, inference, and experimentation
  • Improving data warehouse design and performance within AWS Redshift, including refactoring poorly structured data
  • Integrating new and underused data sources to unlock additional value
  • Supporting feature store development and data pipelines for A/B testing and analytics tools
  • Optimising data systems for cost, performance, reliability, and data freshness
  • Contributing to greenfield initiatives while scaling existing data infrastructure handling very high volumes of event data

Your Skills and Experience

  • Strong commercial experience building production grade data pipelines using Python and SQL
  • Hands on experience with AWS data services such as S3, Redshift, Glue, Athena, and streaming technologies like Kinesis
  • Experience working with large scale, high velocity event data and understanding the trade offs around cost, performance, and reliability
  • Ability to think beyond implementation and understand how data supports business and product outcomes
  • Comfortable collaborating across Data, Engineering, and Product in a fast moving environment
  • Exposure to ML or analytics use cases, including preparing data for modelling or experimentation, is highly beneficial

What They Offer

  • Clear scope for progression as the data platform and team continue to scale

How to Apply

If you are interested in building high impact data systems in a growing SaaS environment, apply now to find out more about this opportunity.

Related Jobs

View all jobs

AWS Data Engineer

83zero Tower Hamlets, London, United Kingdom
£60,000 – £70,000 pa Hybrid Clearance Required

AWS Data Engineer

Bis Henderson Leicestershire, United Kingdom
£70,000 – £80,000 pa Hybrid

AWS Data Engineer - Telecom

Beat My Salary London, United Kingdom

AWS Data Engineer - Snowflake Cortex

Opus Recruitment Solutions London, United Kingdom
Contract

Data Engineer - AWS | London Insurance

Opus Recruitment Solutions London, United Kingdom

Senior AWS Data engineer (LDW Data Warehouse Discovery)

Experis Telford, Shropshire, SY2 5TN, United Kingdom
£400 – £480 pd

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Advertising data engineering jobs in the UK requires a different approach to most technical hiring. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.