At a Glance
- Tasks: Design and build data pipelines on AWS for real-time decision making.
- Company: Fast-growing UK tech scale-up focused on privacy-first digital marketing solutions.
- Benefits: Hybrid work model, clear progression opportunities, and a collaborative culture.
- Other info: Join a dynamic team working on greenfield projects with high ownership.
- Why this job: Shape modern data infrastructure and make a real impact in a scaling SaaS business.
- Qualifications: Experience with Python, SQL, and AWS data services; strong collaboration skills.
The predicted salary is between 50000 - 65000 £ per year.
Manchester (hybrid, 2 days in the office)
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.
AWS Data Engineer in Manchester employer: Harnham Search & Selection
Join a dynamic and innovative technology scale-up in Manchester, where you will have the opportunity to shape cutting-edge data infrastructure that drives real-time decision making and machine learning initiatives. With a strong focus on employee growth, a collaborative engineering culture, and the chance to work on greenfield projects, this role offers a unique environment for those looking to make a significant impact while enjoying the benefits of a hybrid working model.
Contact Details:
Harnham Search & Selection Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AWS and data pipelines. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to data engineering. Think about how you've tackled challenges in past projects and be ready to discuss them in detail.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace AWS Data Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your experience with AWS data services and any relevant projects you've worked on. We want to see how you can contribute to our data infrastructure!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about this role and how your background aligns with our needs. Share specific examples of your work with data pipelines and machine learning to show us what you bring to the table.
Showcase Your Technical Skills:Don’t shy away from detailing your technical expertise! Mention your experience with Python, SQL, and any AWS services you've used. We love seeing candidates who can demonstrate their hands-on experience with real-world applications.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Let’s get started on this journey together!
How to prepare for a job interview at Harnham Search & Selection
✨Know Your AWS Inside Out
Make sure you brush up on your knowledge of AWS data services like S3, Redshift, Glue, and Kinesis. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience building production-grade data pipelines using Python and SQL. Have specific examples ready that demonstrate your ability to design and optimise data ingestion processes, especially in a high-velocity environment.
✨Understand the Business Impact
It's crucial to convey how data supports business outcomes. Think about how your work has influenced decision-making or improved performance in previous roles. Be prepared to discuss how you can contribute to measurable commercial outcomes in this new position.
✨Collaborate and Communicate
Since this role involves working closely with Data Science, Engineering, and Product teams, be ready to share examples of how you've successfully collaborated across different functions. Highlight your communication skills and your ability to thrive in a fast-paced environment.
