National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Director of Data Engineering

Zendr
Newcastle upon Tyne
3 months ago
Applications closed

Related Jobs

View all jobs

Director Of Data Engineering

Director Of Data Engineering

Director Of Data Engineering

Director Of Data Engineering

Director Of Data Engineering

Director Of Data Engineer

Our client is aSeries Afunded SaaS startup specializing in Threat Intelligence. They leverage advanced machine learning for narrative intelligence, helping enterprises and government agencies combat social media manipulation and emerging narrative threats. Their platform processes vast amounts of unstructured, cross-channel media data, converting it into actionable insights.


They are looking for a Director of Data Engineering expert to spearhead their development, implementation, and advancement of their data infrastructure. In this role, you will work closely with the Data, Product, and Engineering team.


Will be tasked with managing 2 people initially then scale into consolidated Data team whilst you will be reporting into the VP of Engineering.


Key Responsibilities:

  • Develop and implement a long-term vision for data engineering and DevOps strategies.
  • Collaborate with senior leadership to prioritize initiatives, set objectives, and define measurable outcomes.
  • Build, mentor, and lead a diverse team of Data Engineers
  • Oversee the design, development, and maintenance of scalable data pipelines, warehouses, and processing frameworks.
  • Lead adoption of modern DevOps methodologies to streamline CI/CD pipelines and deployment processes.
  • Partner with cross-functional teams, including product, analytics, and engineering, to align technical solutions with business needs.
  • Present project updates, performance metrics, and strategic initiatives to leadership.


Required Qualifications:

  • 10+ years of engineering experience, with at least 5+ years in data engineering
  • Proven experience in designing and implementing data architectures, ETL processes, and DevOps pipelines.
  • Expertise in cloud platforms AWS, Azure, or GCP.Preferably AWS
  • Experience with modern DevOps tools such as Kubernetes, Docker, Terraform, Jenkins, or similar.
  • Track record of successfully managing and scaling high-performing technical teams.
  • Experience with data orchestration platforms such as Dagster or Airflow.
  • Strong database architecture design skills for both structured and unstructured data.
  • Advanced knowledge of Elasticsearch or OpenSearch, including configuration and search functionalities.
  • Ability to define and communicate data architecture requirements while staying up to date with best practices.
National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.