Data Engineer in Northampton

Data Engineer in Northampton

Northampton Full-Time 60000 - 80000 £ / year (est.) No working from home possible
hackajob

At a Glance

  • Tasks: Design and build high-quality data products that drive business success.
  • Company: Join Barclays, a leading financial institution with a commitment to innovation.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Collaborative environment with strong focus on continuous improvement and career development.
  • Why this job: Make a real impact by engineering data solutions that power critical business outcomes.
  • Qualifications: Experience in cloud data engineering and proficiency in PySpark and SQL.

The predicted salary is between 60000 - 80000 £ per year.

Join us at Barclays as a Data Engineer, where you will design, build, and operate high-quality, reusable data products that power critical business outcomes.

In this role you will engineer and manage end-to-end data product lifecycles—from ingestion and transformation to serving—across pipelines on the data platform.

You will ensure that data products are trusted, well-governed, discoverable, and fit for purpose, with clear ownership, defined SLAs, and embedded controls.

  • You Will Be Responsible For
  • Designing and delivering scalable, production-grade data products aligned to business capabilities and use cases
  • Embedding data quality, lineage, observability, and metadata standards to support auditability and regulatory compliance
  • Ensuring timely, secure, and governed access to data through well-defined interfaces and contracts
  • Collaborating with product owners, architects, and domain teams to align data products to business outcomes and platform strategy
  • Supporting the evolution of our data product operating model, enabling reuse, interoperability, and consistent delivery across domains

Your work will directly enable reliable, outcome-driven data products, accelerating value delivery within the Product domain, and beyond.

To be successful as a Data Engineer, you should have experience with

  • Cloud Data Engineering Expertise – Ability to design and build scalable, production-grade data products on AWS (Glue, Athena, S3, Databricks), managing batch pipelines and ETL/ELT processes in alignment with defined SLAs, data contracts, and reuse standards.
  • Programming & Query Languages – proficiency in Py Spark and SQL to develop robust transformations, automate data product pipelines, and deliver high-quality, consumable data assets.
  • Data Pipeline Design & Optimisation – Ability to engineer and optimise end-to-end data product pipelines, ensuring data quality, reliability, lineage, observability, and security are embedded by design to meet regulatory and business requirements.
  • Some Other Highly Valued Skills May Include
  • Cost-Aware Engineering & Fin

Ops: Optimize storage and compute for sustainable scale.

  • Infrastructure-as-Code & Dev

Ops: Skills in Gitlab, automated deployments, and environment provisioning.

  • Data Visualisation & BI Tools: Ability to support reporting engineers with Tableau or similar tools for end-to-end delivery.
  • Experience working within Barclays Agile ways of working, contributing to iterative delivery of data products aligned to business capabilities and measurable outcomes.
  • Agile Tooling: Strong experience using Jira to manage backlog, ensure traceability from business capabilities to data products, and support governed delivery.

This role is based in Northampton.

Purpose of the role

To build and maintain systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.

  • Accountabilities
  • Build and maintain data architectures pipelines that enable the transfer and processing of durable, complete, and consistent data.
  • Design and implement data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
  • Develop processing and analysis algorithms fit for the intended data complexity and volumes.
  • Collaborate with data scientists to build and deploy machine learning models.
  • Analyst Expectations
  • Perform prescribed activities in a timely manner and to a high standard, consistently driving continuous improvement.
  • Have in-depth technical knowledge and experience in the assigned area of expertise.
  • Possess thorough understanding of the underlying principles and concepts within the area of expertise.
  • Lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
  • If the position has leadership responsibilities, demonstrate a clear set of leadership behaviours: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others.
  • Or, as an individual contributor, develop technical expertise, acting as an advisor where appropriate.
  • Have an impact on the work of related teams within the area.
  • Partner with other functions and business areas.
  • Takes responsibility for end results of the team’s operational processing and activities.
  • Escalate breaches of policies / procedure appropriately.
  • Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
  • Advise and influence decision making within own area of expertise.
  • Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to.

Deliver work and areas of responsibility in line with relevant rules, regulation and codes of conduct.

  • Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisation’s products, services and processes within the function.
  • Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
  • Make evaluative judgements based on the analysis of factual information, paying attention to detail.
  • Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
  • Guide and persuade team members and communicate complex / sensitive information.
  • Act as contact point for stakeholders outside the immediate function, while building a network of contacts outside team and external to the organisation.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right.

They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

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Data Engineer in Northampton employer: hackajob

At hackajob, we pride ourselves on being an exceptional employer that fosters a culture of innovation and inclusivity. Our diverse team thrives in a high-performance environment where your contributions directly impact our multi-asset platform's success. With ample opportunities for professional growth and a commitment to employee development, joining us means being part of a forward-thinking company that values your expertise and ambition.

hackajob

Contact Details:

hackajob Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer in Northampton

Get Involved in Data Science Meetups

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Show Off Your Projects

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hackajob.

Apply Directly through Our Website

When you find a suitable opening like Data Engineer at hackajob, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Engineer in Northampton

SQL
Python
Data Pipeline Development
Problem-Solving Skills
Data Engineering
Communication Skills
API Integration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at hackajob, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hackajob. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at hackajob

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hackajob!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.