Consulting Data Engineer

London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer (AD -Consulting) - Exclusive

Lead Data Engineer (AD -Consulting) - Exclusive

Lead Data Engineer (AD -Consulting) - Exclusive

Lead Data Engineer (AD -Consulting) - Exclusive

Lead Data Engineer (AD -Consulting) - Exclusive

Principal Data Engineer - AWS

Certain Advantage are recruiting on behalf of our growing London based Data & AI consulting client who specialist in providing best in class support to clients who use Palantir's Foundry, Gotham, and AIP as part of their architecture.

A large proportion of projects involve solving problems in the defence domain, so SC clearance is required, and we can only consider candidates eligible and willing to obtain this.

We're looking for data professionals who get excited about engaging with users to understand and break down complex novel problems, and design and deliver data solutions to solve important problems.

Prior experience in the Palantir AIP, Foundry and Gotham would be advantageous. Previous development experience in PySpark, Typescript and front end frameworks like React would also be advantageous.

As a Consultant Engineer your responsibilities will include

Assist in the design, development, and maintenance of data pipelines and ETL processes to build data and action models to address the workflow needs.
Build and edit operational workflows, including front ends and decision-support toolsets, inclusive of native Palantir tooling and integrated front ends.
Collaborate with team members to implement AI and machine learning models against user problems.
Engage in continuous learning and developmentThis is a permanent position requiring onsite working in London with potential for 1 day remote working per week.

Does this sound like your next career move? Apply today!

Working with Certain Advantage

We go the extra mile to find the best people for the job. If you're hunting for a role where you can make an impact and grow your career, we'll work with you to find it.

We work with businesses across the UK to find the best people in Finance, Marketing, IT and Engineering.

If this job isn't for you, head to (url removed) and register for job alerts and career guidance tips

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.