Graph Data Engineer (Neo4j)

Amber Labs
London
4 months ago
Applications closed

Related Jobs

View all jobs

Only 24h Left: Data Scientist / AI Engineer

Data Engineer

Data Engineer

Data Engineer

AI Engineer

Senior Cloud Engineer (AWS)

Graph Data Engineer (Neo4j) – EUC Nuclear

The Company: 

At Amber Labs, we are a cutting-edge UK and European technology consultancy that prioritises empowering autonomy, promoting experimentation, and facilitating rapid learning to provide exceptional value to our clients. Our company culture is centred around collaboration, where all colleagues, regardless of their role, work together to minimise risk and shorten delivery times. Our team consists of highly-skilled cross-functional consultants, analysts, and support staff.

We are seeking a skilled and experienced Graph Data Engineer specializing in Neo4j and related graph database technologies to join our End-User Computing (EUC) team within the Nuclear Sector. The ideal candidate will play a critical role in designing, developing, and optimizing graph data models, with a focus on supporting complex nuclear engineering processes and systems. You will work closely with data scientists, architects, and cross-functional teams to deliver robust data solutions tailored to the nuclear industry's strict regulatory and safety requirements.

Key Responsibilities:

  • Design, develop, and optimize graph database models using Neo4j to meet the needs of EUC systems in the nuclear domain.
  • Collaborate with nuclear engineers, data scientists, and IT teams to understand data requirements and translate them into scalable graph data structures.
  • Ensure data integration from diverse sources into graph databases, leveraging APIs, ETL pipelines, and other data tools.
  • Develop and maintain Cypher queries to manipulate and analyze graph data.
  • Perform performance tuning on graph databases to ensure efficiency and reliability in a high-demand environment.
  • Work with cloud platforms (Azure, AWS, GCP) and on-premise solutions to deploy, maintain, and manage the graph data infrastructure.
  • Implement and monitor data security policies, ensuring compliance with nuclear sector regulations, particularly around data privacy, security, and governance.
  • Collaborate with DevOps teams to ensure smooth integration and CI/CD deployment of graph databases and associated tools.
  • Troubleshoot and resolve database issues, ensuring data accuracy, reliability, and availability for critical nuclear projects.
  • Provide technical guidance and training to junior engineers and other stakeholders on graph data concepts and Neo4j tools.
  • Stay up to date with the latest trends and innovations in graph database technologies, recommending upgrades and new tools as appropriate.

Essential Skills and Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
  • Proven experience working with graph databases, especially Neo4j (3+ years preferred).
  • Strong expertise in Cypher query language and hands-on experience with graph data modeling and analysis.
  • Experience with ETL tools for data extraction, transformation, and loading into graph databases.
  • Familiarity with cloud platforms (Azure, AWS, GCP) for deploying and managing database solutions.
  • Solid understanding of DevOps principles, including CI/CD pipelines, containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
  • Strong knowledge of data security practices, particularly within regulated environments such as nuclear or other critical infrastructure sectors.
  • Experience working in End-User Computing (EUC) environments and with diverse end-user datasets.
  • Proficiency in one or more programming languages such as Python, Java, or JavaScript.
  • Experience with data visualization tools and techniques for representing graph data (e.g., Neo4j Bloom).

Benefits:

  • Join a rapidly expanding start-up where personal growth is a part of our DNA.
  • Benefit from a flexible work environment focused on deliverable outcomes.
  • Receive private medical insurance through Aviva.
  • Enjoy the benefits of a company pension plan through Nest.
  • 25 days of annual leave plus UK bank holidays.
  • Access Perkbox, a global employee rewards platform offering discounts, perks, and wellness resources.
  • Participate in a generous employee referral program.
  • A highly collaborative and collegial environment with opportunities for career advancement.
  • Be encouraged to take bold steps and embrace a mindset of experimentation.
  • Choose your preferred device, PC or Mac.

Diversity & Inclusion:

Here at Amber Labs, we are dedicated to fostering an inclusive and equitable workplace for all. Our commitment to diversity, equality, and inclusion includes:

Valuing the unique experiences, perspectives, and backgrounds of all employees and creating an environment where everyone feels welcomed, respected, and valued.

Prohibiting all forms of harassment, bullying, discrimination, and victimisation and promoting a culture of dignity and respect for all.

Educating all new hires on our Diversity and Inclusion policies and ensuring they are aware of their rights and responsibilities to create a safe and inclusive workplace.

By taking these steps, we are dedicated to building a workplace that reflects and celebrates the diversity of our employees and communities.

At Amber Labs, all employees are required to meet the Baseline Personnel Security Standard (BPSS). Please be advised that, at this time, we are unable to consider candidates who require sponsorship or hold a visa of any type.

What Happens Next?

Our Talent Acquisition Team will be in touch to advise you on the next steps. We have a two-stage interview process for most of our consultants. In certain cases, we may include a third and final stage, which is a conversation with the company Partners. This will only be considered if deemed necessary.

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.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.