Data Engineer

Ignite Digital Talent
Reading
5 months ago
Create job alert
About the Role

We are looking for a Data Engineer / Analyst to join our growing data team. This is a fantastic opportunity to work on cutting‑edge Azure data solutions, helping to shape and deliver high‑quality, scalable data platforms that drive real business insights.

What You’ll Be Doing
  • Designing, building, and maintaining ETL pipelines using Azure Data Factory, SSIS, and SQL Server
  • Developing and optimising stored procedures and queries for data transformation and integration
  • Building and maintaining data warehouse solutions and dimensional data models
  • Supporting data integration projects and ensuring data quality, accuracy, and consistency
  • Delivering insights through Power BI dashboards and reports
  • Using Python and PowerShell for automation and data manipulation
  • Collaborating with business stakeholders to translate requirements into technical data solutions
What We’re Looking For
  • Strong experience with SQL Server (T‑SQL, stored procedures, optimisation)
  • Hands‑on expertise with Azure Data Factory (ADF) and SSIS
  • Solid understanding of data warehousing and dimensional modelling
  • Proven experience building ETL/data integration solutions
  • Exposure to Power BI, Python, and PowerShell is highly desirable
  • Financial services or insurance experience is desirable but not essential
  • Excellent problem‑solving skills with a proactive, can‑do attitude
  • Strong communication skills and ability to work closely with stakeholders
Why Join Us?
  • Flexible hybrid working - only 1–2 days per month required in the Reading office
  • Opportunity to work with modern Azure data technologies
  • A collaborative, supportive team culture where your ideas are valued
  • Clear pathways for career progression and development
  • Competitive salary and benefits package including 10% bonus, private medical & generous pension
How to Apply

If you’re a Data Engineer or Data Analyst with strong SQL, ADF, and SSIS experience, we’d love to hear from you!

Equal Opportunities

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, gender, age, disability, or other protected characteristics.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.