Head of Engineering

she does data.
London
1 day ago
Create job alert

Head of Data Engineering & Analytics

We are seeking a Head of Data Engineering & Analytics to play a pivotal role in leading cutting-edge data infrastructure initiatives. In this dynamic position, you will shape the future of insurtech utilizing advanced technologies and adhering to industry best practices with tools such as Azure, Snowflake, dbt, and more.

What you’ll be doing:

  • Develop and execute a comprehensive data strategy that aligns with our business goals and enhances decision-making processes.
  • Champion the integration of high-quality, accessible data throughout our operations to promote a culture of data-driven decision making.
  • Recruit, mentor, and lead a top-tier data engineering and analytics team, emphasizing innovation, efficiency, and collaborative growth.
  • Manage significant expansions in data volume and integration, enhancing our product offerings with superior data insights.
  • Lead robust data governance practices, collaborating closely with compliance and other stakeholders to uphold data integrity and utility.
  • Design, develop, and maintain sophisticated data models and architectures that inform business strategies and operational efficiencies.
  • Spearhead the development and management of robust data pipelines in collaboration with technical teams and data scientists, supporting both pre-processing and post-processing activities.

What you can bring:

  • A minimum of 10 years’ experience in data engineering and analytics, with a proven ability to guide and grow high-performing teams.
  • Strong background in data governance and the scaling of data operations.
  • Demonstrated leadership in transformative data-driven projects and team development.
  • Expertise in data modelling, database design, and data warehousing.
  • Proficiency in SQL, Python, and other essential data manipulation technologies.
  • Experience in deploying complex machine learning algorithms in partnership with data science teams.

What would be advantageous:

  • Experience in implementing observability and monitoring frameworks.
  • Active engagement in open-source projects or tech communities.
  • Experience in fast-paced, high-growth startups.
  • Knowledge of the insurance industry.

What’s in it for you:

  • Competitive share options scheme.
  • Generous pension plan and enhanced parental leave.
  • 25 days of holiday plus public holidays.
  • Flexible, hybrid working.
  • Financial support for professional development and continuous learning.
  • Home office stipend and mental health support initiatives.
  • Cycle to work scheme and dedicated time for professional growth.
  • Company-provided MacBook.

Mirai believes in the power of diversity and the importance of an inclusive culture. We welcome applications from individuals of all backgrounds, understanding that a range of perspectives strengthens both our team and our partners teams. This is just one of the ways that we’re taking positive action to shape a collaborative and diverse future in the workplace.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Data Infrastructure and Analytics

J-18808-Ljbffr

Related Jobs

View all jobs

Head of Engineering

Head of Engineering Engineering · London, Edinburgh ·

Head of Engineering Engineering · London, Edinburgh ·

Head of Engineering

Head of Data - Engineering - AI & Data Science

Head of Data Engineering & Architecture

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.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.