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

Apply Now

Senior Data Engineer

Amtis - Digital, Technology, Transformation
Birmingham
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer – Azure Platform


Overview

Amtis is proud to be recruiting for an exciting opportunity to join a forward-thinking data team. This role is ideal for a technically skilled and proactive data engineer passionate about building scalable, secure, and high-performing data solutions in Azure. You’ll play a key role in shaping the data strategy, enhancing platform capabilities, and supporting business intelligence initiatives.


Key Responsibilities

  • Design and develop Azure data pipelines using Data Factory, Databricks, and related services.
  • Implement and optimize ETL processes for performance, reliability, and cost-efficiency.
  • Build scalable data models and support analytics and reporting needs.
  • Design and maintain Azure-based data warehouses and data lakes.
  • Ensure data governance, security, and compliance with GDPR and other regulations.
  • Collaborate with cross-functional teams to gather requirements and deliver solutions.
  • Manage Azure SQL databases, including performance tuning and monitoring.
  • Monitor and maintain data infrastructure, resolving issues proactively.
  • Document technical designs and share knowledge through training and code reviews.
  • Contribute to big data analytics and machine learning initiatives.
  • Continuously improve platform performance and adopt new Azure capabilities.


Requirements

  • Strong experience with Azure Databricks.
  • Proficient with Azure Data Factory, Synapse Analytics, Data Lake Storage, Stream Analytics, and Event Hubs.
  • Skilled using Python, Scala, C#, .NET, and advanced SQL (T-SQL).
  • Experience with CI/CD pipelines using Azure DevOps and infrastructure as code (Terraform, BICEP, ARM).
  • Solid understanding of data engineering, distributed computing, and cloud-native design.
  • Experience in data modelling, metadata management, and data quality practices.
  • Strong communication and stakeholder engagement skills.
  • Self-starter with a proactive mindset and ability to overcome challenges.
  • Empathetic and collaborative team player open to new ideas and technologies.
  • Desirable: Machine learning engineering knowledge.


Midlands based opportunity

Hybrid working – 1 day on-site per week

Salary package - £60,000-£65,000

Great benefits package on offer


If you’re interested in this opportunity, and have full right to work in the UK, please apply with you updated CV.


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.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.