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

Apply Now

Azure Data Engineer

Reading
8 months ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

A top Managed Services Provider are on the lookout for an Azure Data Engineer to join their expanding applications team. In this role, you'll support a crucial reporting project and play a key part in driving business transformation with the latest Microsoft cloud technologies.

The ideal candidate will have extensive experience as a data engineer within large organisations and enterprise platforms.

This opportunity is ideal for someone who enjoys staying up-to-date with technology through active involvement in solution delivery and is keen to advance their career by enhancing their skills in digital transformation.

Key Responsibilities:

Collaborate on enterprise-level projects.
Deliver hands-on solutions to internal clients.
Stay updated with technology trends and actively participate in solution delivery.Ideal Candidate:

Technical Skills:

Proficiency in Azure Data Platform (Data Lake, Synapse Analytics, SQL Database, Data Factory).
Strong knowledge of Power BI and Microsoft reference architectures.
Experience in Data Platform Design and Azure DevOps.
Familiarity with Dynamics 365 ERP and CRM data models.
Understanding of Azure data integration technologies and Modern Workplace.Experience:

3+ years in Data & Analytics.
Agile delivery methods.
Mentoring junior staff.
Deploying Azure solutions using CI/CD pipelines.
Data integration, analysis, modelling, cleansing, and enrichment.
Large-scale ERP/CRM implementations.
Working with remote teams.
Proficiency in SQL and Python.
Knowledge of Data Governance, including MDM and Data Quality tools.Remote based.

Up to 60k basic + good benefits

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.