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

View Open Roles

Data Engineer

Derby
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

About Us

Makutu designs, builds and supports Microsoft Azure cloud data platforms. We are a Microsoft Solutions Partner (Azure Data & AI) and are busy building a talented team with relevant skills to deliver industry leading data platforms for our customers.

The Role

The Data Engineer role is key to building and growing the in-house technical team at Makutu. The role will provide the successful applicants with the opportunity for significant career development while working with a range of large businesses to whom data is critical to their success.

Working as part of the team and with the customer, you'll require excellent written and verbal English language and communication skills.

Big growth plans are in place to build a broader and deeper technical capability with a focus on the Microsoft Azure technology stack.

The position of Data Engineer is a key role in the wider capability of our team. Occasional visits to our Head Office and customers sites will be required.

Key responsibilities:

  • Identify, design, and implement working practices across data pipelines, data architectures, testing and deployment

  • Understand complex business requirements and providing solutions to business problems

  • Understand modern data architecture approaches and associated cloud focused solutions

  • Defining data engineering best practice and sharing across the organisation

  • Collaborating with the wider team on data strategy

    Skills and experience:

  • A relevant Bachelors degree in Computing, Mathematics, Data Science or similar (ideal but not essential)

  • A Masters degree in Data Science (ideal but not essential)

  • Experience building data pipelines with modern practices including the use of cloud native technologies, DevOps practices, CI/CD pipelines and agile delivery

  • Experience with data modelling, data warehousing, data lake solutions

  • Able to communicate effectively with senior stakeholders.

    Successful candidates will likely posses Azure certifications such as DP-600 and/or DP-700.

    Also, applicants will have experience working with some of the following technologies:

  • Power BI

  • Power Apps

  • Blob storage

  • Synapse

  • Azure Data Factory (ADF)

  • IOT Hub

  • SQL Server

  • Azure Data Lake Storage

  • Azure Databricks

  • Purview

  • Power Platform

  • Python

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.

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.

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.