Managing Data Architect

Trust In SODA
united kingdom, united kingdom
10 months ago
Applications closed

Related Jobs

View all jobs

Data Warehouse Manager

Senior Data Engineer - Azure, BI & Data Strategy

Senior Data Engineer - Azure, BI & Data Strategy

Senior Data Architect

Data Engineer - AWS | London Insurance

Data Lead - Data Transformation Programme

💼 Managing Data Architect

👔 Consultancy

📍 London, Manchester, Glasgow

💵 £90-100k

📦 £12k annual bonus, Travel Expenses, Certs Scheme, 10% Combined Pension, Private Medical, Uncapped Progression


Do you want to work for one of the country's top consultancies on some brand new high profile digital transformations?


Do you want to get rapidly accredited (AWS, Azure, GCP) for free whilst also using these skills commercially too?



I am partnered with one of the World’s Top Tech Consultancies who are partnered with many of the biggest names in the Private and Public Sector.

They have just won a couple of exciting new projects and are looking for aManaging Data Architectto join their team and assist with the continued scaling and optimisation of these.

Their ideal candidate would have 10+ years experience in Data Engineering/Architecture and have good knowledge within:


  • Cloud (AWS, GCP, Azure)
  • Data Warehousing (Snowflake, Redshift, BigQuery)
  • ETL (Data Fabric, Data Mesh)
  • DevOps (IaC, CI/CD, Containers)
  • Leadership / Line Management
  • Consulting / Client Facing Experience

In return they would be offering

  • £12k annual bonus
  • Free Certification Scheme (ServiceNow, TOGAF)
  • Uncapped Progressions (Just hit the criteria and you will continually climb the ranks)
  • Travel expenses
  • Up to 10% combined pension
  • Private Medical
  • Flexi Benefits (Life Assurance, GIP, Dental etc.)
  • Hybrid Working (onsite 30% worst case)
  • Overseas Conference Budget


If you’re passionate about Data Architecture and keen to work on some really exciting projects in a client-facing capacity then please apply right away!

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

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.