Sustainability Advisor

Northampton
10 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Principal Data Engineer

Data Architect

Principal Data Engineer

Senior Power BI Data Analyst

CGEMJP00330718 Lead Data Engineer

Sustainability Advisor / Sustainability Analyst (Embodied Carbon) – Civils / Infrastructure –

Role is a mix of Northampton office, site visits and remote work.

Also open to consider candidates from other construction roles who have a passion for sustainability with a view of transferring into a full-time sustainability role, such as design engineers, design coordinators, design manager, site engineers or other

Exciting opportunity for a permanent Sustainability Coordinator / Sustainability Consultant to join one of the UK's most successful Tier 1 building & civil engineering main contractors, with a very stable and fast growing forward order book.

BEST EMPLOYER IN CONSTRUCTION
This company have one of the best opportunities on offer for a Sustainability Advisor in the industry.

What makes it great?

-Very low staff turnover, in fact ridiculously low, must be one of the lowest in the industry. Excellent sign that they look after their staff.

-Professional & friendly team environment, even on site!

-Excellent relationships and a prompt payer to subcontractors and suppliers.

-High standards of excellence on site,

-Big enough to keep you busy, but small enough to know your name, excellent option if you are fed up with being treated like just another number.

-Excellent opportunity for career progression, going through a period of organic growth.
-Excellent salary and benefits package including, car allowance / competitive pension / x 2 bonuses a year.

ROLE

As Sustainability Advisor your role will include

• Coordinating the data collection for LCA reporting requirements

• Coordinating client and project sustainability / carbon / ESG reporting requirements.

o Liaising with Commercial Team / Design Team / Project Team to obtain

information and analysing procurement schedules / drawings / commercial.

documents.

o Liaising with the supply chain / external stakeholders to obtain procurement and

site operations information for LCAs.

• Understanding LCA & Net Zero frameworks/ standards and working within these

guidelines

o Reviewing and keeping up to date with the latest published standards and

guidelines from UKNZBS / UKGBC / RICS / ICE / PAS 2080 etc

• Ensuring the use of appropriate evidence for reporting and to maintain accurate data.

• Liaising with other departments to improve the collection, input, and reporting of

Sustainability and ESG data.

• Assisting with development of Civils & Infrastructure Net Zero reporting processes

• Working in line with client requirements / sustainability targets

• Capturing best practice through case studies to share information and improve

performance.

• Guiding project teams on reporting timeframes internally and to Clients/ Stakeholders

• Aligning to the sustainability branding on all materials, presentations, and documents

• General Sustainability / NZ / CSR support

• Acting as a Sustainability / CSR champion within the business

• Ensuring data quality for emissions reporting.

• Influencing design and build processes to hit Net Zero targets.

• Generating innovative ideas to help reduce project’s carbon emissions.

• Supporting company targets to achieve its sustainability targets.

• Staying up to date with new technology, innovations, and best practice in the industry to

accelerate sustainability progress.

• Weekly site visits

REQUIREMENTS:

To be considered for this Sustainability Advisor role you must meet the following criteria:

-Previous work in a Sustainability Advisor / Coordinator / Sustainability Consultant or similar role.

-Also open to consider candidates from other construction roles who have a passion for sustainability with a view of transferring into a full-time sustainability role, such as design engineers, design coordinators, design manager, site engineers or other*

-Either previous experience on Civil engineering (Highways / Rail or Infrastructure) projects or alternatively a civil engineering related qualification.

-Genuine passion for sustainability.

-Open to consider candidates previous employed by a main contractor, sun contractor or consultancy.

REMUNERATION:

The successful Sustainability Advisor will receive:

*Competitive Basic (Dependent on experience)
*Car Allowance
*Pension
*Bonus.

To be considered for this vacancy or to find out more information please apply now.

Services advertised by Talk Recruitment are that of an employment business and/or agency.

If you have not had a reply on your application within five working days, please assume your application has been unsuccessful on this occasion

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 Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.