Data Engineering manager

TRIA
Birmingham
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

BDO Digital Data Architecture and Engineering Senior Manager/Director

BI and Data Engineering Lead

BI and Data Engineering Lead

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Lead Data Scientist

Senior Data Engineering Manager

Snowflake | AWS/Azure | Data transformation

Up to £110,000 + 20% Bonus + 10% Pension

Milton Keynes – Two/Three days a month on site.


This Senior Data Engineering opportunity is to join a rapidly growing financial services organisation, who are going through a large Data Transformation. Your role will report into the CDO and you will play a pivotal role in transforming data for the business.


You’ll help lead a greenfield project to design, build, and implement a robust Snowflake data warehouse from the ground up. As both a hands-on and strategic leader, you’ll guide the data engineering team in architecting scalable solutions while driving best practices in data engineering, cloud migration, and data quality. Alongside hands-on engineering work, you will mentor a small team, contributing to their technical and professional development, while also helping shape the future of the data engineering practice and the organization’s broader data strategy.


For this role you will:

  • Lead the end-to-end migration of on-premises data systems to Snowflake, ensuring efficient and secure data transformation.
  • Help develop and implement a comprehensive Data Engineering strategy that aligns with business objectives and enhances data accessibility, quality, and governance.
  • Serve as a technical lead in both architecture and development, providing guidance on best practices in Snowflake schema design, data pipeline development, and integration.
  • Have advanced skills in SQL and Python, with the ability to build and optimize complex data pipelines and manage large datasets.
  • Domain Experience – Insurance/financial services. However, we will consider applications outside of these industries


You will receive:

  • Salary up to £110,000
  • Extremely competitive benefits package that includes up to 20% bonus, private medical, 10% pension
  • Hybrid working – 2/3 days in the office a month.


If you are interested and would like to find out more, please apply!

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.

Careers

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.

Jobs

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.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.