Senior Data Engineer

Hays
Oxford
4 months ago
Create job alert

Your new company



While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
An established and fast-growing technology organisation is on a mission to transform digital connectivity across the UK. With a focus on building and operating high-speed fibre networks, the business is committed to delivering world-class broadband services to communities and supporting a data-driven future. You'll be joining a forward-thinking environment that values innovation, collaboration, and continuous improvement.


Your new role


As a Senior Data Engineer, you will play a pivotal role in shaping and enhancing the organisation's enterprise data platform. Working within a specialist Data Analytics & AI team, you'll be responsible for designing, building, and maintaining scalable data pipelines and models within Snowflake to support analytics, reporting, and data-led decision-making across the business.You will translate data architecture strategies into high-quality technical solutions, optimise performance and cost, and ensure the data platform is reliable, secure, and well-structured. This includes developing ELT/ETL pipelines using tools such as dbt and Argo Workflows, implementing data quality and governance practices, and leveraging advanced Snowflake features to drive automation and efficiency.Collaboration is key-you'll work closely with analysts, data consumers, and business stakeholders, enabling them through well-designed data models and providing technical support where needed. You'll also contribute to monitoring, CI/CD processes, and ongoing improvements to engineering standards across the team.


What you'll need to succeed

  • Proven experience delivering cloud-based data engineering solutions, ideally centred around Snowflake
  • Strong skills in SQL, Python, and dbt for data modelling and transformation
  • Experience with Snowflake RBAC and performance optimisation
  • Familiarity with ingestion/replication tools such as Airbyte, Fivetran, Hevo, or similar
  • Understanding of cloud technologies (AWS preferred)
  • Knowledge of data modelling, governance principles, and best-practice engineering standards
  • Experience supporting BI/reporting tools such as Power BI
  • Solid grounding in version-controlled development and CI/CD practices (git)

Desirable:

  • Exposure to enterprise systems like Salesforce, BSS/OSS, telephony, or call-centre data
  • Experience in data platform migrations, data validation, and quality assurance
  • Background in enabling business teams through training, documentation, or adoption support
  • Familiarity with Terraform or Infrastructure-as-Code
  • A mindset for continuous learning and staying up to date with modern data stack tooling


What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career. xrnqpay

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be


Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.