Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Engineer

Nucleus Global
united kingdom
2 months ago
Create job alert

Inizio, the world’s leading healthcare and communications group providing marketing and medical communications services to healthcare clients. We have 5 main divisions within the group Medical, Advisory, Engage, Evoke and Biotech. Our Medical Division focuses on communicating evidence on new scientific and drug developments and educating healthcare professionals and payers on the appropriate use of therapy.

We have a fantastic opportunity for a Data Engineer to support the build of AI capabilities across Inizio Medical.

Key Responsibilities

  1. Build scalable and efficient data pipelines.
  2. Design the Data Architecture (including data models, schemas, and data pipelines) to process complex data from a variety of data sources.
  3. Build and maintain the CI/CD infrastructure to host and run data pipelines.
  4. Build and maintain data APIs.
  5. Setup, support, interact with and maintain AI components including generative and machine learning models.
  6. Build mechanisms for monitoring the data quality accuracy to ensure the reliability and integrity of data.
  7. Evaluate and make technical decisions on the most suitable data technology based on business needs (including security, costs, etc).
  8. Collaborate with Data Scientists, Data Analysts, Software development and other stakeholders to understand data requirements.
  9. Work closely with System Admins and Infrastructure teams to effectively integrate data engineering platforms into wider group platforms.
  10. Be cognisant of new and emerging technologies related to data engineering, and be an active champion of data engineering.
  11. Monitor and optimise performance of data systems, troubleshoot issues, and implement solutions to improve efficiency and reliability.
  12. A strong proficiency in Python.
  13. Experience working with Generative AI models, their deployment and orchestration.
  14. A solid understanding of database technologies and modelling techniques, including relational databases and NoSQL databases.
  15. Experience with setting and managing Databricks environments.
  16. Competent working with Spark.
  17. Solid understanding of data warehousing modelling techniques.
  18. Competent with setting up CI/CD / DevOps pipelines.
  19. Experience with the cloud platforms Azure and AWS and their associated data technologies is essential.
  20. Experience and understanding of graph technologies and modelling techniques is desirable.
  21. Experience with GCP and Scala is desirable.
  22. Excellent communication skills, capable of explaining complex data/technical concepts to stakeholders with varying levels of technical awareness.
  23. Ability to work collaboratively.

In addition to a great compensation and benefits package including private medical insurance and a company pension, we are happy to talk dynamic working. We are also known for our friendly and informal working environment and offer excellent opportunities for career and personal development.

Don't meet every job requirement? That's okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role, but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

Apply for this job
#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.

Automate Your Machine Learning Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

ML jobs are everywhere—product companies, labs, consultancies, fintech, healthtech, robotics—often hidden in ATS portals or duplicated across boards. The fastest way to stay on top of them isn’t more scrolling; it’s automation. With keyword-rich alerts, RSS feeds, and a reusable ChatGPT workflow, you can bring relevant roles to you, triage them in minutes, and tailor strong applications without burning your evenings. This is a copy-paste playbook for www.machinelearningjobs.co.uk readers. It’s UK-centric, practical, and designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning LLM/NLP, Vision, Core ML, Recommenders, MLOps/Platform, Research/Applied Science, and Edge/Inference optimisation. Shareable Boolean searches you can paste into Google & job boards to cut noise. Always-on alerts & RSS feeds delivering fresh roles to your inbox/reader. A ChatGPT “ML Job Scout” prompt that deduplicates, scores fit, and outputs tailored actions. A lightweight pipeline tracker so deadlines and follow-ups never slip.