Senior Data Engineering Consultant

Staines
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineering Consultant

Senior Data Engineering Consultant

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

SAS Data Engineer

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Senior Data Engineering Consultant
 
This leading boutique Data & Insights Consultancy are going from strength to strength and are seeking a Senior Data Engineering Consultant to join their high-performing team.
 
This is a fantastic opportunity to apply your strong hands-on data engineering skills across a wide variety of challenging projects, and deliver value-adding data and analytics solutions that make a true business impact.
 
Role & Responsibilities
This Data & Insights practice is made up of some of the most competent and highly skilled data professionals in the market, and you will get the opportunity to work with and learn from some of the best.
 
As a Senior Data Engineering Consultant you will utilise your functional and hands-on technical data engineering skills to implement end-to-end reporting, analytics and data solutions for a variety of different customers, from large enterprises to small start-ups.
 
You will get to work on and lead exciting and complex projects that vary in size and complexity, and you will take ownership of deliveries; gathering requirements, understanding business problems, designing and building solutions, reporting and analysis through to go-live and training. You will have plenty of opportunity to flex your broad, hands-on, data skills to help harness solutions and solve problems, and you will have the opportunity to witness the change and impact your work has on the client.
 
Responsibilities will include:

Building and implementing technical data solutions for customers using a variety of different data tools and platforms
Consulting with clients on approach, and suitable technologies
Technical project leadership, requirements gathering, delivery and documentation
Writing code and building solutions
Managing junior consultants on deliveries 
What is required?
To be considered, you will be a Technical Data Consultant or Data Engineer who has a track record of delivering data solutions, ideally in a client facing consultancy environment.
 
You will have a strong hands-on technical skillset spanning data engineering, data integration and data migration and will be adaptable, able to work with different tools and technologies, depending upon the client and project needs.
 
You will possess strong stakeholder engagement and management skills and will be able to evidence where you have led or at least played a key role in the delivery of data solutions, managing projects and mentoring or overseeing the work of more junior colleagues.
 
You will bring experience in designing data solutions, writing code, and documentation, and must have strong skills in tools including but not limited to:
 
MS Fabric stack
Databricks
Azure
SQL
Tableau / Power BI
 
A knowledge of data modelling and of general IT architecture and systems integration is also required. Other technologies such as Azure Data Factory, RedShift, Informatica, Qlik or similar are also useful and you will be tech curious, keen and open-minded to learning new skills. Experience in Oracle OBIEE and/or Oracle Analytics Cloud is desirable.
 
A self-starter, you will also need excellent communication and presentation skills.
 
Rewards
 
A competitive salary of £60,000-£80,000 is on offer (depending on your level of experience) as well as an annual bonus of £5k-£7k (paid quarterly), private medical, pension (up to 5% matched) and other perks such as a mobile phone allowance.
 
This is a hybrid role that offers lots of flexibility to work remotely, but visits to the office in Surrey are required once er week (as well as occasional visits to the office in London Bridge).
 
This consultancy has big ambitions to grow, so if you are a Senior Data Engineering Consultant and want to work alongside some of the industry’s best on some exciting client projects, then this could be the challenge you are seeking!

If you are interested please apply ASAP. The People Network is an employment agency and will respond to all applicants within three - five working days. If you do not hear within these timescales please feel free to get in touch

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.