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

Apply Now

Azure Data Engineer

Softcat
Manchester
3 days ago
Create job alert
Azure Data Engineer

Softcat – Manchester, England, United Kingdom


Would you like to kick start your career in a supportive, collaborative and innovative company? Do you enjoy working as part of an enthusiastic, passionate, and collaborative team? As one of the UK's leading IT infrastructure providers and a FTSE 250 listed company, Softcat has built a reputation for excellence. Our strategy is simple – we believe that highly engaged employees are the key to building customer trust and loyalty, enabling us to invest in technology and services capabilities.


Responsibilities

  • Design, develop, test, and maintain robust, reusable data pipelines using Azure Data Factory (orchestration), Azure Databricks (transformations in PySpark/Spark SQL), and DBT (SQL‑based modelling).
  • Prepare, clean, and transform unstructured and semi‑structured data for LLM training, fine‑tuning, and prompt engineering workflows.
  • Develop Python‑based ETL/ELT scripts, data transformation utilities, and automation tools.
  • Implement CI/CD pipelines using Azure DevOps and Databricks Asset Bundles for data workflows, promoting automation, reproducibility, and minimal manual intervention.
  • Collaborate with Data Scientists, AI/ML Engineers, and Analysts to optimise the flow of data into ML and LLM models.

Qualifications

  • Strong hands‑on experience with Azure Data Factory (pipelines, triggers, parameterisation, linked services).
  • Strong hands‑on experience with Azure Databricks (PySpark, Spark SQL, Delta Lake, performance tuning).
  • Strong SQL development skills, including performance tuning and working with large datasets.
  • Proficiency with Python for data engineering tasks (Pandas, PySpark, data cleaning, API integrations).
  • Proficiency with DBT (data modelling, macros, testing, documentation).
  • Experience with Azure DevOps for Git‑based source control and deployment pipelines for data solutions.

Flexible Working

  • Hybrid working.
  • Working flexible hours – flexing the times you start and finish during the day.
  • Flexibility around school pick‑up and drop‑offs.

We recognise that everyone is different and that the way in which people want to work and deliver at their best is different for everyone. In this role, we can offer the following flexible working patterns.


If you have a disability or neurodiversity, we can provide support or adjustments that you may need throughout our recruitment process or any mitigating circumstance you wish for us to consider. Any information you share on your application will be treated in confidence.


Learn more about life at Softcat and our commitments to diversity and inclusion at jobs.softcat.com/jobs/our-culture/


#J-18808-Ljbffr

Related Jobs

View all jobs

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

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.