Data Engineer in Oxford

Data Engineer in Oxford

Oxford Full-Time 45000 - 55000 € / year (est.) No home office possible
Aurora Energy Research

At a Glance

  • Tasks: Build and maintain data pipelines, transforming data for business insights.
  • Company: Join a fast-growing, data-driven organisation with a collaborative culture.
  • Benefits: Enjoy private medical insurance, parental support, and local discounts.
  • Other info: Flexible hybrid working options to suit your lifestyle.
  • Why this job: Dive into modern data tools and tackle real-world business challenges.
  • Qualifications: Experience in SQL, Python, and cloud-based data platforms is essential.

The predicted salary is between 45000 - 55000 € per year.

We are seeking a Data Engineer to join our growing Business Data team within Internal Technology. The role will focus on building, maintaining, and evolving a centrally governed business data platform, supporting analytical and operational use cases across the organisation. Working closely with Senior and Lead Data Engineers, as well as business stakeholders, you will contribute hands‑on to data ingestion, transformation, and modelling activities using our core data platform technologies. This role is well suited to someone who enjoys translating business data requirements into robust, scalable data solutions and wants to deepen their experience in an enterprise data environment. You will operate in a collaborative, intellectually stimulating environment, with exposure to modern cloud‑native data tooling and real‑world business problems in a fast‑growing, data‑driven organisation.

Key Responsibilities

  • Build and maintain reliable data pipelines to ingest and transform data from enterprise systems, including finance, CRM, HR, and collaboration platforms.
  • Develop and manage data transformations to support business intelligence and analytical use cases.
  • Contribute to the design and implementation of dimensional and analytics‑friendly data models.
  • Work with senior engineers to implement data engineering best practices, standards, and governance controls.
  • Support data quality, validation, and monitoring processes to ensure trusted reporting and insights.
  • Collaborate with analysts, engineers, and business stakeholders to understand reporting requirements and translate them into technical solutions.
  • Contribute to documentation, data lineage, and technical knowledge sharing across the team.

Skills, Knowledge and Expertise Required attributes:

  • Experience delivering data engineering solutions in a production environment.
  • Practical experience with:
    • SQL for data transformation and modelling.
    • Python for data processing or orchestration.
    • Cloud‑based or modern data platforms (e.g. Microsoft Fabric or equivalent).
  • Experience ingesting data from relational databases and/or SaaS platforms via APIs.
  • Understanding of core data engineering concepts such as:
    • Data quality and validation.
    • Basic data governance principles.
  • Strong analytical and problem‑solving skills, with attention to detail.
  • Good communication skills, with the ability to work effectively with technical and non‑technical stakeholders.
  • Ability to manage tasks independently while contributing effectively within a team.
  • Exposure to PySpark or notebook‑based data development.
  • Familiarity with enterprise systems such as ERP, CRM, or HR platforms.
  • Experience working in a governed, multi‑environment (DEV / TEST / PROD) data platform.
  • Awareness of CI/CD or DevOps practices for data engineering.
  • Interest in building scalable and maintainable data platforms in a fast‑growing organisation.

What we offer

  • Private Medical Insurance.
  • Parental Support.
  • Employee Assistance Programme (EAP).
  • Local Oxford Discounts.
  • Cycle‑to‑work Scheme.
  • Flu Jabs.

At AER, we are committed to offering flexibility in the way we work. Most of our roles are hybrid with a mix of in‑office/home working and potentially adjustable working hours. Let’s discuss what works for you and AER during the interview process. The Company is committed to the principle that no employee or job applicant shall receive unfavourable treatment on grounds of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage or civil partnership, pregnancy, and maternity.

Data Engineer in Oxford employer: Aurora Energy Research

At AER, we pride ourselves on being an excellent employer, offering a collaborative and intellectually stimulating environment for our Data Engineers. With a strong focus on employee growth, we provide access to modern cloud-native data tools and the opportunity to work on real-world business challenges, all while enjoying benefits like private medical insurance, parental support, and a flexible hybrid working model tailored to your needs.

Aurora Energy Research

Contact Detail:

Aurora Energy Research Recruiting Team

StudySmarter Expert Advice🤫

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

Tip Number 1

Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. Getting to know someone inside the company can give you insights and maybe even a referral.

Tip Number 2

Prepare for the interview by brushing up on your technical skills. Practice SQL queries and Python scripts, and be ready to discuss your past projects. We want to see how you tackle real-world data challenges!

Tip Number 3

Showcase your problem-solving skills during interviews. Be ready to walk us through your thought process when faced with data issues. We love candidates who can think on their feet and come up with creative solutions.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at AER.

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

SQL
Python
Cloud-based Data Platforms
Data Ingestion
Data Transformation
Data Modelling
Data Quality and Validation

Some tips for your application 🫡

Tailor Your CV:Make sure your CV speaks directly to the Data Engineer role. Highlight your experience with SQL, Python, and any cloud-based platforms you've worked with. We want to see how your skills align with our needs!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Don’t forget to mention specific projects or experiences that relate to the job description.

Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled data challenges in the past. We love seeing candidates who can think critically and come up with innovative solutions, so don’t hold back!

Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!

How to prepare for a job interview at Aurora Energy Research

Know Your Data Engineering Basics

Before the interview, brush up on core data engineering concepts like data quality, validation, and governance principles. Be ready to discuss how you've applied these in past projects, as this will show your understanding of the role's requirements.

Showcase Your Technical Skills

Prepare to demonstrate your practical experience with SQL and Python. Have examples ready where you've used these tools for data transformation or orchestration. If you’ve worked with cloud-based platforms like Microsoft Fabric, make sure to highlight that too!

Understand the Business Context

Familiarise yourself with the types of enterprise systems mentioned in the job description, such as finance, CRM, and HR platforms. Being able to translate business data requirements into technical solutions will impress your interviewers and show that you can think from a business perspective.

Communicate Effectively

Practice explaining complex technical concepts in simple terms. You’ll likely be working with both technical and non-technical stakeholders, so being able to communicate clearly is key. Prepare some scenarios where you successfully collaborated with others to solve problems.