Consulting Data Engineer

London
3 weeks ago
Create job alert

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

Related Jobs

View all jobs

AWS Lead Data Engineer

Senior Data Engineer

Senior Data Analyst - RELOCATION TO ABU DHABI

Senior Data Engineer

Azure Data Engineer

Graduate Data Engineer x 3 (STEM) - Graduate Scheme - Training & Development - Bristol - New (REFBJ18)

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.

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.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.