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

Apply Now

Microsoft Data Solution Architect

Belfast
6 months ago
Applications closed

Related Jobs

View all jobs

Machine learning and AI Engineer

Machine learning and AI Engineer

Machine Learning and AI Engineering Lead

Strategic Insight Data Science Lead

Strategic Insight Data Science Lead

Data Science Consultant

Microsoft Data Solutions Architect needed for a permanent opportunity for a leading Microsoft Partner.

Key Role Responsibilities

  • Articulate Data Value: Understand and communicate the value data brings to an organization in alignment with business goals.

  • Design and Development Leadership: Lead the design and development of data solutions, including coding, testing, and defect resolution.

  • Hands-on Development: Actively develop components of data solutions.

  • Requirement Identification: Identify and translate functional, technical, and non-functional requirements into user stories for the team.

  • Performance Management: Manage performance, optimize costs, and execute unit and integration testing for data pipelines and reports.

  • Customer and Team Advisory: Advise on effort estimation and technical implications of user stories, manage work breakdown from inception to delivery, and oversee the team's backlog.

  • Customer Relationship Management: Maintain key relationships with decision-makers, including CxOs, throughout project delivery.

  • Industry Trends Awareness: Stay updated on trends in data science and engineering, including techniques, competitors, partners, and technology.

  • Continuous Improvement: Promote best practices and continuous improvement in data solutions.

  • Ability to do a Tender

    Education, Qualifications, and Skills

  • Experience: 5+ years in data roles.

  • Technical Skills:

    • Development experience with Microsoft (Azure) technologies, including Azure Data Factory, Synapse, and Power BI, or relevant ETL tools.

    • Expertise in Microsoft Fabric or Databricks

    • Experience with technology partners or consulting organizations is highly desirable.

    • Leadership experience in technical teams (engineers, analysts, architects) for data-intensive systems.

    • Proficiency in SQL or SQL extensions for analytical use cases.

    • Deep understanding of distributed data stores and data processing frameworks.

    • Ability to communicate technical designs clearly, both written and verbally.

    • Proficiency in designing analytical and operational data models.

    • Background in Data Architecture, Engineering, or Analytics with knowledge of modern enterprise architecture patterns.

    • Proven track record in delivering data-oriented solutions, including data warehousing, operational insight, data management, or business intelligence.

  • Certifications: Azure/Databricks data certifications are desirable.

    If you want the opportunity to take your career to the next level, please apply now

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.