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

Apply Now

Accelerant | Data Engineer

Accelerant
Manchester
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer - Collibra | Insurance Domain

Data Engineer

AWS Data Engineer

Data Scientist

Data Scientist

Data Scientist

About Accelerant:

Accelerant is a data-driven, technology-powered insurance platform that empowers underwriters to better serve their insureds. Their advanced data intelligence tools are revolutionizing how underwriters share and exchange risk, with a focus on the niche needs of small and medium-sized businesses. Their risk exchange platform supports a curated network of top-tier underwriting teams, providing deep insights into insurance pools with a diversified portfolio that minimizes catastrophic, systemic, and aggregation risks. They're proud of their AM Best A- (Excellent) rating, which reflects their commitment to excellence in the insurance industry.


Accelerant is developing a cutting-edge platform to revolutionize how risk is exchanged in the future. Our Product & Technology (P&T) organization is seeking an experienced Analytics Engineer to manage high value data to provide insights, value, and security to Accelerants clientele..


How will you spend your time

  • Designing and implementing data pipelines and models, ensuring data quality and integrity.
  • Solving challenging data integration problems, utilizing optimal patterns, frameworks, query techniques, sourcing from vast and varying data sources.
  • Building, maintaining, and optimizing our Data Warehouse to support reporting and analytics needs.
  • Collaborating with product managers, business stakeholders and engineers to understand the data needs, representing key data insights in a meaningful way.
  • Staying up-to-date with industry trends and best practices in data modelling, database development, and analytics.
  • Optimizing pipelines, frameworks, and systems to facilitate easier development of data artifacts.


You will be successful if you have

  • A deep desire to build, model and maintain high value data to maximize usability and access to the insights that data generates.
  • Good experience in Kimball/dimensional modelling &/or Data Vault.
  • Several years experience in building and maintaining Data Warehouses for reporting and analytics.
  • Strong skills in SQL, Python, problem-solving and data analysis.
  • Strong background in Insurance and/or Dbt.
  • Communicate and collaborate well both on technical and product levels.
  • An eagerness to learn and collaborate with others, learn quickly and are able to work with little supervision.



If you're interested in this opportunity, please send across your CV to .

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.