Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior/Lead Data Engineer

Aurora Energy Research
Oxford
1 week ago
Create job alert
Senior/Lead Data Engineer

Department: Internal Technology

Employment Type: Permanent - Full Time

Location: Oxford, UK

Reporting To: Head of Architecture and Engineering

Description

Based in Oxford, you will be joining the growing business data team within Internal Technology. Working to the Head of Architecture and Engineering you will take primary ownership of delivering the business data solution with the agreed technology stack, Microsoft Fabric. You will liaise with senior business stakeholders to define functional specifications for business intelligence reports that deliver to agreed technology standards. You will represent these functional specs through Technical Design Authority and take a hands‑on role in delivering the required data infrastructure with the rest of the team to enable the reporting insights. As the practice senior you will also be involved in defining processes and practices to ensure they are scalable, secure and robust.

You will work in a creative, intellectually stimulating environment. You will enjoy autonomy, and the opportunity to have a significant impact on Aurora’s data strategy, ensuring that our business intelligence can draw on all our enterprise effectively and meet the needs of this very fast growing, data heavy business.

Key Responsibilities
  • Work as the data lead within the Architecture and Engineering function to build a centrally managed, governed, data layer to provide insight across our enterprise software systems, including Microsoft Dynamics 365 F&O, Salesforce, SharePoint, SAP SuccessFactors (HRMS), and new systems that are needed as the company grows
  • Steer key decisions on how they integrate and how data flows between the systems to ensure we have an extensible, well managed eco‑system which enables the business to work efficiently and effectively as it grows and does not obstruct data insights being leveraged cross‑system
  • Work with internal teams to understand what challenges they face, particularly in their reporting requirements, where technology can have an impact
  • Put in place policies and practices to ensure our business data layer is scalable, secure and robust
  • Guide junior members of the team in how to deliver technically and effectively
What we are looking for

Required attributes:

  • Minimum of 2 years’ experience delivering data solutions to organisations including:
    • Extraction of data from traditional database systems and online systems via API
    • Transformation of data to support tactical and broad business insight requirements
    • Dimensional modelling
    • Data governance
    • Demonstrable experience with: Microsoft Fabric, Python/PySpark, Notebooks, SQL, SaaS and API based data extraction
  • Proven ability to analyse and manipulate complex numerical and business data
  • Excellent time management, organisational skills and and attention to detail
  • Strong communication
  • Confidence working with varied business stakeholders, excellent interpersonal skills with ability to build relationships at all levels
  • Delivery oriented, happy to role‑up your sleeves to get things done, positive can‑do attitude

Desirable attributes:

  • Experience with reporting from any of our existing Tier 1 systems (Dynamics 365 Finance and Operations, Salesforce CRM, SAP SuccessFactors, Entra ID)
  • Experience with delivering Direct Lake data architectures with Microsoft Fabric
  • Experience with utilising CI/CD patterns and DevOps tooling to orchestrate configuration across environments
  • Experience working with Power BI (including Power Query and DAX)
  • Experience working with Logic Apps, Power Platform
What we offer

Some of the benefits we include are:

  • Private Medical Insurance
  • Dental Insurance
  • Parental Support
  • Salary‑Exchange Pension
  • 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.

To apply, please submit your Résumé / CV, a personal summary, your salary expectations and please inform us of your notice period.

Unfortunately, we are unable to accept applications via email, telephone, or social media platforms. To be considered for this position, please submit your application using the link provided. Applications submitted through any other channel will not be reviewed.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Lead Data Engineer

Senior/Lead Data Engineer (PySpark, AWS)

Lead Data Engineer

Senior Scientific Data Engineer

Lead Data Engineer

Lead/Senior Data Scientist

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.