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

Apply Now

Data Engineer - Senior Consultant

Avanade
Manchester
7 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Our talented Data Engineering team is made up of globally recognised experts - and there’s room for more analytical, innovative, client-driven data professionals. If you’re passionate about helping clients make better data-driven decisions to tackle their most complex business issues, let’s talk. Take your skills to a new level and launch a career where you can truly do what matters.

As a member of the Data Engineering team, you’ll have access to the research, knowledge, and tools to create leading-edge solutions across Avanade’s Data & AI practice. The role of Data Engineer is perfect for ambitious technologists passionate about working with the latest Microsoft Fabric and / or Azure Databricks technologies to deliver modern, highly scalable data platforms for all our client’s analytics and AI needs. Our clients look to us for innovation, which means you’ll have early access to the latest technologies so you can master them and stay ahead of the curve. Demonstrable end-to-end experience in Data Engineering, including large-scale projects Experience in working with the latest Azure technologies, such as; Databricks, Microsoft Fabric, Data Factory, Azure Data Lake Storage (Gen 2), Purview, Cosmos DB, Open AI, Azure ML, AI Foundary, Kubernetes, Understanding of software engineering tools and concepts including experience in Python, Scala or PySpark, database technologies, data modelling and SQL Confident communicator who is able to explain technical terms to non-technical audiences and mentor junior colleagues Leads small development teams: track work, manage assignments, manage capacity, etc. Characteristics that can spell success for this role Analytical, curious, agile Team player and good communicator Problem-solver, patient, quality-driven Self-motivating Innovative mindset Design, development, and delivery of enterprise-grade analytics solutions based on Azure and Databricks technologies Evangelise and evolve best practices for our clients and our team including to mentor your colleagues, supporting their personal development Constantly developing technical skills in the latest Azure and Databricks technologies - achieving & maintaining relevant certifications Working directly with high profile clients across a variety of sectors to understand their requirements and present solutions to customer sponsors 

Some of the best things about working at Avanade

Opportunity to work for Microsoft’s Global Alliance Partner of the Year (14 years in a row), with exceptional development and training (minimum 80 hours per year for training and paid certifications) Real-time access to technical and skilled resources globally Collaborate with some of the brightest “Microsoft minds” Build your expertise, solve problems, learn, and develop

Find out more about some of our benefits Employee Benefits at Avanade | Avanade



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.

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.