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

Apply Now

Construction & Engineering Data Analyst - Built Environment

Panoramic Associates
East Sussex
1 month ago
Applications closed

Related Jobs

View all jobs

Group ICT Data Analyst

Data Analyst

Real Estate and Workplace Data Analyst

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer. Job in Glasgow Education & Training Jobs

CANDIDATES WITH NO CONSTRUCTION OR ENGINEERING EXPERIENCE NEED NOT APPLY

Data Analyst / Data Engineer - Built Environment
South West base with weekly travel to a major project site near Oxford

Hybrid working available - 3 days on site

A Built Environment Consultancy are seeking a Data Analyst / Data Engineer to join their Digital Engineering function, supporting data-driven delivery across major engineering and construction projects. This role is suited to someone technically strong, Power BI-literate, and comfortable working in a construction or infrastructure environment with a digital / data bias.

What you will be doing
* Developing, maintaining and optimising data pipelines and warehousing for project data
* Extracting, cleaning and transforming large datasets to support reporting and decision-making
* Designing and delivering dashboards and self-service reporting (Power BI essential)
* Working with BIM, GIS, IoT and other digital tools to embed data into project delivery
* Ensuring data governance, integrity and security across the full data lifecycle
* Automating repetitive tasks to drive productivity and consistency
* Working with multidisciplinary stakeholders to embed data-led thinking in project workflows

What you'll need
* Proven experience in data analysis / engineering, ideally in construction, infrastructure or the built environment
* Strong literacy in Power BI and competency in Python / SQL or similar
* Experience with data warehousing or cloud environments (Azure / AWS / GCP)
* Ability to turn complex data into clear, actionable outputs for project teams
* Strong communication skills and comfort working with engineering stakeholders

Desirable
* Experience of BIM, GIS or digital engineering toolsets
* Appreciation of data science concepts and methods
* Prior experience in a consultancy environment (large management consultancy backgrounds ideal)
* Ability to lead a data analytics service stream

If this sounds suitable for you, or someone you know, please send an updated CV and contact number to Sean Cloherty at Panoramic Associates so we can discuss further.

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 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.

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.