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

Apply Now

Snowflake Data Engineer

Kubrick
City of London
5 days ago
Create job alert

Required Skill: Python; Snowflake; Snowflake Champion (Certified)


Location: Mansion House, Greater London, EC4, United Kingdom


Job Type: NA


Job Description / Summary

At Kubrick, we’re not just a consultancy - we’re building the next generation of Data and AI leaders. Since 2017, we’ve helped leading organisations harness the power of data, AI, and cloud, and now we’re looking for a Snowflake Data Engineer to join our growing team.


The Role: As a Snowflake Data Engineer, you’ll play a pivotal role in designing, developing, and deploying cutting-edge cloud data platforms and analytics solutions. You’ll combine hands-on engineering with technical leadership, shaping data strategies and delivering impactful, scalable solutions for our clients.


Responsibilities

  • Lead technical delivery on client projects, ensuring quality and scalability
  • Translate complex business requirements into robust Snowflake solutions
  • Build and optimize ELT pipelines with tools like dbt, Airflow, and Fivetran
  • Implement secure and efficient Snowflake environments with best-in-class practices
  • Collaborate with stakeholders to influence data strategy and architecture
  • Mentor and guide junior engineers while driving engineering excellence

What We’re Looking For / Qualifications

  • Proven experience in data engineering or analytics
  • Strong Snowflake expertise (or similar cloud data warehouses)
  • Solid SQL, ELT, and data modelling skills
  • Hands-on experience with Python and cloud platforms (AWS/Azure/GCP)
  • Familiarity with modern data pipelines, CI/CD, and version control
  • Strong communicator and problem solver with proven leadership experience

We Offer

  • Salary: c60k & bonus
  • Hybrid: 2-3 days a week in the office
  • Friendly and collaborative working environment
  • Access to upskilling opportunities and clear progression path
  • 25 days of annual leave
  • Highstreet discounts and Wellness Hub with confidential well-being and mental health support
  • Cycle to work scheme & eye-care vouchers

Diversity, Equity and Inclusion (DEI)

At Kubrick, we not only strive to bridge the skills-gap in data and technology, but we are also committed to playing a key role in improving diversity in the industry. To that effect, we welcome candidates from all backgrounds, and particularly encourage applications from groups currently underrepresented in the industry, including women, people from black and ethnic minority backgrounds, LGBTQ+ people, people with disability and those who are neurodivergent. We are committed to ensuring that all candidates have an equally positive experience, and equal chances for success regardless of any personal characteristics. Please speak to us if we can support you with any adjustments to our recruitment process. We’ve proudly partnered with Women in Data for over six years, providing a community platform for our female and non-binary consultants to upskill, access mentoring opportunities, and build their professional networks. Through this partnership, we’ve also supported mission-critical pro bono projects to improve lives through data and AI, including research into women’s health and safety


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Snowflake Data Engineer

Senior Snowflake Data Engineer

Data Engineer - Informatica & Snowflake Copy

Data Engineer - Informatica & Snowflake

Lead Data engineer

Vice President, Senior 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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.