Senior Geo-Environmental Engineer

Derby
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

MMM Data Scientist

Sales Data Analyst

Marketing Data Analyst

Lead Data Analyst

My client is pleased to announce that due to continued growth there is
an opportunity for a Senior Geo-Environmental Engineer to join the team based in
Derby.
 
MAIN DUTIES AND RESPONSIBILITIES
 
The main duties and responsibilities of the role will be to develop and manage the work
and staff of the Derby team and to assist the Directors to exploit business
opportunities.
 
You will be expected to support colleagues to deliver the work of the department and
to assist and mentor more junior members of staff. You will work within a team
environment and will also benefit from the support of more senior and more junior
members of staff. The work will be a combination of office and site based work.
 
Duties will include (but not limited to):
·Undertaking site appraisals to include review of 3rd party reports.
·Design and cost Phase 2 site investigations.
·Undertake and contribute to Phase 1 desk studies, Phase 2 site investigation,
·Remediation Strategies and Validation work as required.
·Undertake site work as and when required to include logging of soils and rock
·to BS/Eurocode, sampling, monitoring and scheduling.
·Project management to include ensuring projects are delivered in accordance
·with the require scope of works within budget and to ensure more junior
·members of staff are aware of their responsibilities and undertake their work
·in a safe and competent manner.
·Be able to interpret data and undertake report writing to a suitable professional
·standard.
·Competent in undertaking human health risk assessments, controlled water
·risk assessments, preferably Detailed Quantitative Risk Assessment.
·Demonstrate a basic understanding of soil mechanics and recommend
·appropriate foundation designs.
·Develop the company's expertise and offerings.
·Liaise with clients and develop client relationships.
 
QUALIFICATIONS, SKILLS AND EXPERIENCE
Candidates will be expected to:
·Have a minimum degree level qualification in an appropriate engineering or
·science discipline.
·Ideally hold a post graduate qualification.
·Working towards and ideally be close to gaining chartered status.
·Have previous relevant experience.
·Be computer literate in MS Word, Excel, Openground, Surfer, MS Project,
·preferably CAD and/or GIS.
·Be able to demonstrate excellent interpersonal skills for management of both
·internal staff and clients.
·Be able to demonstrate a suitable level of H&S and QA, preferable hold a CITB
·Managers safety training scheme card.
·Full UK Driving license.
·Be able to demonstrate their right to work in the UK
 
WHAT THEY OFFER
The remuneration will be agreed on an individual basis, but they will offer a competitive
salary, personal pension, an attractive working environment; informal flexible working arrangements; employee engagement to include bi-annual appraisal to identify training requirements and career progression routes; payment of professional membership fees; min 25 days leave with an extra day for each year work up to 28 days maximum plus bank holidays; holiday buy back scheme; long service awards; and more

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.

Careers

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.

Jobs

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.

Education

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.

🍪 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.