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

Apply Now

Azure Data Engineer

KDR Talent Solutions
Manchester
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

This range is provided by KDR Talent Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from KDR Talent Solutions

Data & Analytics Recruiter - Supporting companies in hiring the best professionals in Data, Digital & Analytics

Azure Data Engineer | Location: Manchester (Hybrid - 1-2 days a month in office) | Salary: £55,000-£65,000

The Opportunity

Are you passionate about building cutting-edge data platforms that drive business growth? Our client is seeking a skilled and motivatedData Engineerto play a key role in the creation of abrand-new data platformwithin theMicrosoft Azure and Fabricecosystem.

This is an exciting opportunity to be at the forefront of data innovation, working within a newly formedData & Reportingteam. You’ll help shape the data strategy, improve data quality, and empower the business to make data-driven decisions.

As a Data Engineer, you'll work closely with both technical and business stakeholders, leveraging your expertise to design, develop, and optimize ahigh-performance data platform. This platform will be built to scale, incorporating the latest advancements in data intelligence while supporting strategic business objectives.

Key Responsibilities

  1. Build & Develop– Design and maintain a robustAzure-based Data Platform, ensuring performance, scalability, and availability.
  2. Data Pipelines– Connect APIs, databases, and data streams to the platform, implementing ETL/ELT processes.
  3. Data Integrity– Embed quality measures, monitoring, and alerting mechanisms.
  4. CI/CD & Automation– Create deployment pipelines and automate workflows.
  5. Collaboration– Work with stakeholders acrossGlobal IT, Data, and Reportingteams to translate business requirements into technical solutions.
  6. Futureproofing– Drive the evolution of the data platform, ensuring adaptability for new data sources, analytical models, and emerging technologies.

What You’ll Bring

  1. Extensive hands-on experiencewithMicrosoft Azure data tools(must-have: Azure Data Factory, Azure Synapse, or Azure SQL).
  2. Dimensional modellingexpertise for analytics use cases.
  3. Python scriptingexperience for data automation.
  4. Experience withCI/CD methodologiesfor data platforms.
  5. Knowledge ofMS SQL Server, SSIS, Visual Studio, and SSDT projects.
  6. Hands-on experience withMicrosoft Fabric.
  7. Familiarity withSalesforceand/orWorkday.
  8. Previous experience in a relevant industry.

Why Join?

  1. Greenfield Project– Work on an all-new data platform, shaping its architecture from the ground up.
  2. Collaborative Culture– Engage with global teams in an agile, innovative environment.
  3. Career Growth– Play a pivotal role in driving data excellence within a forward-thinking business.
  4. Cutting-Edge Tech– Work with the latest advancements inAzure, Fabric, and Data Engineering.

This is a fantastic opportunity for aData Engineerlooking to make a tangible impact. If you’re ready to take on a challenging and rewarding role, apply today!

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Data Infrastructure and Analytics, IT System Data Services, and IT Services and IT Consulting

#J-18808-Ljbffr

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.