Senior Data Engineer

Fruition Group
London
2 months ago
Create job alert

Job Title:

Senior Data Engineer
Location:

Ipswich (Hybrid)
Salary:

£60,000 - £70,000 + Benefits

Why Apply?

This is a fantastic opportunity to join a growing organisation where data is central to decision-making, automation, and future innovation. You'll play a key role in shaping a modern

data platform and architecture , working across data engineering, modelling, and integration to deliver scalable, high-quality solutions.
The role offers true ownership, allowing you to take projects end-to-end while working with modern technologies such as

Microsoft Fabric, Databricks, and Python

in a collaborative, forward-thinking environment.

Responsibilities

You will design, build, and optimise

data pipelines and integration solutions

that support reporting, analytics, and business operations. This includes developing ETL/ELT workflows using both low-code tools and code-based approaches (SQL, Python, PySpark), ensuring performance, scalability, and reliability across the data platform.
You will take ownership of

data modelling and architecture , designing scalable data warehouse and lakehouse structures, including dimensional models and medallion architectures. You'll ensure data is structured effectively for analytics, reporting, and future AI-driven use cases.
The role also involves managing the

full project lifecycle , from design through to deployment and support, implementing CI/CD pipelines, maintaining documentation, and ensuring strong data governance, quality, and security standards. You'll work closely with stakeholders across the business to translate requirements into robust data solutions.

Requirements

Proven experience as a

Data Engineer delivering end-to-end data solutions

Strong experience with

Microsoft Fabric, Databricks, or similar platforms

Solid understanding of

data modelling (star schema, dimensional modelling, lakehouse design)

Experience building and optimising

ETL/ELT pipelines

using SQL, Python, and/or PySpark

Knowledge of

data governance, quality, and security best practices

Experience implementing

CI/CD pipelines and DevOps practices

Ability to work independently and manage full project lifecycles

Strong analytical, problem-solving, and stakeholder engagement skills

Experience working in

Agile, SCRUM, or Kanban environments

What's in it for me?

You'll have the opportunity to take real ownership of a modern data platform, working with cutting-edge tools while influencing how data is used across the organisation. Alongside a competitive salary, you'll benefit from a supportive and collaborative environment, opportunities for continuous learning, and the chance to work on impactful projects that drive business value.
We are an equal opportunities employer and welcome applications from all suitably qualified individuals regardless of background, identity or circumstance.

TPBN1_UKTJ

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.