Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

Broomedge
2 days ago
Create job alert

Introduction

Our people are what make our family great. As a proud family-run business, we see childcare as a profession, not just a job. We’re passionate about helping our teams grow and be the best they can be!

Kids Planet is a prominent nursery group in the United Kingdom, currently operating at more than 250 locations. Established in 2008 with only 4 sites, the company has experienced substantial growth over the years. We possess extensive data across our applications and are seeking a Data Engineer to develop our platform and data driven approach. We require a dynamic engineer who has experience with Python, SQL, API’s and a passion for all things data.

The Data Engineer will work aside our Lead Engineer to drive development of the data warehouse and data usage in the business. They will maintain and improve our APIs to deliver business value.

If you are a highly motivated individual with some experience but want to grow your career in data engineering along with gaining training and qualifications, then this is the role for you

Key Responsibilities

  • Design and maintain large-scale data processing systems and infrastructure.

  • Create and manage robust data pipelines to collect, clean, and transform raw data into usable formats for analytics and reporting.

  • Collaborate with data analysts, product managers, and software engineers to deliver high-quality data solutions.

  • Monitor data performance to make improvements and automation.

  • Develop and support data warehouse architectures, including ETL (Extract, Transform, Load) processes.

  • Implement best practices for data governance, security, and compliance.

  • Troubleshoot and resolve data-related issues in a timely manner.

  • Stay up to date with the latest industry trends and technologies in data engineering and analytics.

  • Documentation: Maintain thorough documentation of data architecture, processes, and policies.

    Qualifications

  • Education: Bachelor's degree in Computer Science, Information Technology, or a related field;

  • Proven experience as a Data Engineer or in a similar role.

  • Strong proficiency in SQL and at least one programming language such as Python, Java, or Scala.

  • Experience with data modelling, ETL development, and data warehousing solutions

  • Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP)

  • Excellent problem-solving skills and attention to detail.

  • Strong communication and collaboration abilities.

    Nice to Have’s:

  • Knowledge of maintaining API’s between multiple applications

    Benefits

    The company offers great benefits such as:

  • Highly discounted childcare

  • Free breakfast, lunches and healthy snacks including fresh fruit.

  • Birthday Leave

  • Enhanced Maternity, Paternity Fertility and Adoption leave.

  • Fertility Leave

  • Anniversary Awards

  • Employee Assistance Programme

  • Professional Development

  • Career Progression

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.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.