Full Stack Data Engineer (Client Facing)

Decho Group

City of London

3 weeks ago

Applications closed

Related Jobs

View all jobs

Mid Level Data Engineer

Senior Data Engineer

Data Analyst

Geospatial Data Analyst

Junior Data Scientist

Data Engineer - Celonis

About Decho Group

Decho Group is a fast-growing Tech and AI consultancy, founded to solve complex data challenges for governments and enterprises. We specialise in Palantir technologies, advanced analytics, and AI-driven solutions that transform how organisations make decisions.

In October 2025, Accenture acquired Decho Group, recognising our unique ability to combine deep engineering expertise with strategic advisory, tackling mission-critical problems in defence, healthcare, and commercial industries.

Joining Decho means joining a consultancy where AI meets engineering excellence. You’ll be part of a team that thrives on curiosity, collaboration, and bold thinking, working on projects that genuinely change lives and industries.

The Role

We’re seeking Full stack Data Engineers , across all levels from Junior to Senior Manager, who want to apply their technical skills in AI consultancy and Palantir engineering. You’ll design solutions that unify complex data landscapes, build workflows that drive smarter decisions, and partner with clients to deliver sustainable transformation.

This is a hands-on role where you’ll combine software engineering expertise with strategic problem-solving, working across data pipelines, operational workflows, and AI models.

Key Responsibilities

Design & Solve: Break down client problem sets and design innovative solutions using Palantir software.
Engineer Data: Build and maintain pipelines and ETL processes to power decision-making models.
Create Workflows: Develop operational workflows and decision-support tools that transform enterprise operations.
Apply AI: Collaborate with colleagues to implement AI and machine learning models against real-world challenges.
Technical Excellence: Apply your software engineering skills to build scalable, reliable solutions.
Grow & Share: Contribute to the Decho Lab by mentoring peers, upskilling junior engineers, and driving best practice.
Partner with Clients: Build deep, trusted relationships that position Decho–Accenture as their go-to advisor.

What We’re Looking For

Experienced Engineer with proven expertise in Python, SQL, and TypeScript.
Experience with Palantir technologies: Foundry, Gotham, or similar platforms (preferred)
Strong understanding of data engineering, ETL pipelines, and workflow design.
Passion for AI, machine learning, and emerging technologies.
Excellent problem-solving, collaboration, and communication skills.
Curiosity, adaptability, and a drive to make a real-world impact.

Why Join Us

Be part of a fast-growing AI consultancy now backed by Accenture’s global scale.
Work on mission-critical projects across government, defence, health, and commercial sectors.
Gain hands-on experience in AI, advanced analytics, and Palantir technologies.
Shape the future of data-driven decision-making while building your own career story.
Thrive in a culture that values innovation, collaboration, and bold ambition.

Unfortunately we can not provide sponsorship for this opportunity

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Apr 9, 2026

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Mar 24, 2026

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Feb 11, 2026

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.