Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer - Azure

London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Position: Data Engineer - Azure

Location: Remote

Type: 6 Month Contract (Outside IR35)

Rate: £550 to £600 Per Day

Role:

This is a fantastic opportunity to work for a leading Consultancy, my client is currently looking for an experienced Data Engineer to act as client engineer, and architecture lead for various programmes of work.

Data Architect is a multi-disciplinary role, requiring collaboration with a wide range of stakeholders, from developers to C-level executives. You will be responsible for working with customers to influence and shape the end-to-end data management and analytics workstreams, within fast paced and complex programmes, engaging in a wide variety of data management and analytics activities.

Key Responsibilities:

Support and influence Data Strategy, and Data Governance Policies and Principles
Promote Data Management standards and best practices
Support business and data requirements gathering
Input and guidance to business for Data Catalog, Master Data and Metadata Management
Lead the data solution designs and execution of data models for these solutions such as Data Warehouse, Data Lake, and Data Lakehouse
Work with Data Engineers and Analysts to architect scalable and secure solutions across Data Integration, Data Orchestration, Data Processing, Data Storage, and Data Visualisation
Work with cross-functional teams to support delivery of the data solutions
Engage with customer and end-users to understand solution impact and develop technology operation plans
Work with customers or partners to promote the company brand and develop healthy relationships
Coach and mentor upcoming Data Architects

Requirements:

Demonstrable experience in Data Architecture in the last 3 years
Experience in architecting data solutions which meet high data security and compliance requirements
Experience working with various open-source, on-prem, COTS, and cloud (AWS, Azure, GCP) tools and technologies
Advanced Data Modelling skills and experience in relational, dimensional and NoSQL databases
Demonstrable experience in advanced SQL/TSQL
Knowledge and experience working with a variety of frameworks and platforms for data management and analytics
Data Engineering experience, and familiarity with Git, Python and R
Data Analysis, Data Profiling and Data Visualisation experience
Knowledge and desired experience of Big Data

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.