Graduate Data Engineer

Marlow
1 week ago
Create job alert

Role Title: Graduate Data Engineer
Contract: 12 months
Location: Marlow (hybrid)

SRG are working with a leading pharmaceutical company based in Marlow. Our client develops and manufacture an impressive portfolio of aesthetics brands and products. Our client is committed to driving innovation and providing high-quality products and services.

Role Overview

As a Graduate Data Engineer, you will build and maintain scalable data pipelines in Palantir Foundry for advanced reporting and analytics while collaborating with cross-functional teams as part of the BTS Data & Analytics team. You will work closely with key stakeholders in Engineering, Product, GTM, and other groups to help build scalable data solutions that support key metrics, reporting, and insights. You will assist in ensuring teams have access to reliable, accurate data as our company grows. You will have the opportunity to support projects that enable self-serve insights, helping teams make data-driven decisions, while learning from experienced team members and developing your technical and business skills.

Key Responsibilities:

Build and maintain data pipelines, leveraging PySpark and/or Typescript within Foundry, to transform raw data into reliable, usable datasets. Familiarity with Palantir Foundry, PySpark, Kafka, TypeScript, PowerBI preferable.
Assist in preparing and optimizing data pipelines to support machine learning and AI model development, ensuring datasets are clean, well-structured, and readily usable by Data Science teams.
Support the integration and management of feature engineering processes and model outputs into Foundry's data ecosystem, helping enable scalable deployment and monitoring of AI/ML solutions as you develop your skills in this area.
Engaged in gathering and translating stakeholder requirements for key data models and reporting, with a focus on Palantir Foundry workflows and tools.
Participate in developing and refining dashboards and reports in Foundry to visualize key metrics and insights as you grow your data visualization skills.
Collaborate with Product, Engineering, and GTM teams to align data architecture and solutions, learning to support scalable, self-serve analytics across the organization.
Have some prompt engineering experience with large language models, including writing and evaluating complex multi-step prompts
Continuously develop your understanding of the company's data landscape, including Palantir Foundry's ontology-driven approach and best practices for data management.

About you:

You have a degree in Computer Science, Engineering, Mathematics, or similar, or have similar work experience.
Having up to 2 years of experience building data pipelines at work or through internships is helpful.
You can write clear and reliable Python/PySpark code.
You are familiar with popular analytics tools (like pandas, numpy, matplotlib), big data frameworks (like Spark), and cloud services (like Palantir, AWS, Azure, or Google Cloud).
You have a deep understanding of data models, relational and non-relational databases, and how they are used to organize, store, and retrieve data efficiently for analytics and machine learning.
Knowing about software engineering methods, including DevOps, DataOps, or MLOps, is also a plus.You will be considered a strong fit if you have:

Master's degree in engineering (such as AI/ML, Data Systems, Computer Science, Mathematics, Biotechnology, Physics), or minimum 2 years of relevant technology experience.
Experience with Generative AI (GenAI) and agentic systems will be considered a strong plus.
Have a proactive and adaptable mindset: willing to take initiative, learn new skills, and contribute to different aspects of a project as needed to drive solutions from start to finish, even beyond the formal job description.
Show a strong ability to thrive in situations of ambiguity, taking initiative to create clarity for yourself and the team, and proactively driving progress even when details are uncertain or evolving.Other details:

Hybrid working policy: Currently, our client expects all staff to be in their Marlow-based office at least 3 days a week from Jan 2026.
No visa sponsorship. ILR/Citizenship required.

Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy

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.

Neurodiversity in Data Engineering Careers: Turning Different Thinking into a Superpower

Every modern organisation runs on data – but without good data engineering, even the best dashboards & machine learning models are built on sand. Data engineers design the pipelines, platforms & tools that make data accurate, accessible & reliable. Those pipelines need people who can think in systems, spot patterns in messy logs, notice what others overlook & design elegant solutions to complex problems. That is exactly why data engineering can be such a strong fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a data engineering career, you might have heard comments like “you’re too disorganised for engineering”, “too literal for stakeholder work” or “too distracted for complex systems”. In reality, the traits that can make traditional office environments hard often line up beautifully with data engineering work. This guide is written for data engineering job seekers in the UK. We’ll cover: What neurodiversity means in a data engineering context How ADHD, autism & dyslexia strengths map to common data engineering tasks Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data engineering – & how to turn “different thinking” into a genuine professional superpower.

Data Engineering Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the data engineering jobs market in the UK is evolving fast. Almost every organisation is talking about AI, analytics & data-driven decision making – but behind all that sits the data engineering function. Cloud costs, complex data estates, stricter regulation & the explosion of AI workloads are all changing how data platforms are built & run. Some companies are tightening budgets & consolidating teams, while others are doubling down on modern data stacks, lakehouses & real-time pipelines. Whether you are a data engineering job seeker planning your next move, or a recruiter building data teams, understanding the key data engineering hiring trends for 2026 will help you stay ahead.

Data Engineering Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data engineering hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise reliable pipelines, modern lakehouse/streaming stacks, data contracts & governance, observability, performance/cost discipline & measurable business outcomes. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for platform‑oriented DEs, analytics engineers, streaming specialists, data reliability engineers, DEs supporting AI/ML platforms & data product managers. Who this is for: Data engineers, analytics engineers, streaming engineers, data reliability/SRE, data platform engineers, data product owners, ML/feature‑store engineers & SQL/ELT specialists targeting roles in the UK.