Data Architect Engineer DV

Datatech Analytics
City of London
6 days ago
Create job alert

DV Cleared Data Engineers & Data Architects

UK | Hybrid | Multiple levels


At Datatech Analytics, we’re supporting a leading UK technology and consulting organisation delivering mission critical data and AI platforms across defence and national security programmes.


We’re looking to speak with DV-cleared Data Engineers and Data Architects who want to work on complex, high impact programmes where modern data platforms, AI and advanced analytics drive real operational outcomes.


These roles sit within multidisciplinary teams combining engineering, data science and AI expertise, helping organisations transform complex data into secure, scalable and production-ready platforms.


What the work involves

Designing and building production-grade data pipelines across ingestion, processing and consumption.

Working with large structured and unstructured datasets across modern cloud and big data environments.


Architecting secure, scalable data platforms that support analytics and AI-driven decision making.

Collaborating with engineering teams and stakeholders to solve complex technical challenges.


Technology exposure

  • Typical environments include:
  • Python, SQL and modern data engineering tooling
  • Spark, Databricks and distributed data platforms
  • AWS, Azure and Google Cloud
  • Modern data lake and data warehouse architectures


Who we’re keen to speak with

Active DV clearance is essential.


We’re interested in strong engineers and architects across all levels, from hands-on data engineers through to senior architects leading complex platform programmes.

If you enjoy solving complex problems, working with modern data and AI platforms, and operating in fast-paced technical environments, we’d love to hear from you.


If you’re DV cleared and open to hearing about new opportunities, feel free to reach out for a confidential conversation.

Related Jobs

View all jobs

Data Architect Engineer DV

Mid/Senior Data Engineer (Analytics)

Lead Starburst Data Engineer

Data Engineer Founding Role

Principal Data Architect DV Cleared

Data Architect DV Cleared

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.