Pleiad’s story begins over 75 years ago in the insurance sector. Today, Pleiad supports a multifaceted global group, housing a portfolio of companies across RE(insurance), Insurtech, Fintech, Sustainability, and Cybersecurity. Its portfolio companies are licensed and regulated in several countries, staffed by 800+ specialists, and operate from a network of 15+ offices spanning Europe, the Americas, and Asia.
Beyond its role as an umbrella brand, Pleiad provides its portfolio companies with a comprehensive suite of corporate and business consulting services. It acts as a true operating partner, not a passive holder.
Role Purpose
We are looking for an experience Data Engineer to design, build and maintain scalable cloud-based data platforms. You will work closely with analytics, engineering, and business teams to deliver trusted, well-modelled data that supports reporting, insight, and decision-making.
Key Responsibilities
- Build and maintain reliable ELT pipelines using Fivetran, Snowflake, and dbt.
- Develop reusable, tested, and well-documented data models following Kimball and Data Vault principles.
- Write high-quality Python code for data processing, automation, and integration.
- Design and optimise Snowflake data structures, queries, and workloads.
- Deploy and operate containerised data services using Kubernetes on Microsoft Azure.
- Create and maintain CI/CD pipelines for data transformations and platform components.
- Manage source control, branching, pull requests, and code reviews using Git.
- Implement automated data-quality tests, monitoring, and alerting.
- Collaborate with analysts, data scientists, software engineers, and stakeholders to translate requirements into robust data solutions.
- Maintain technical documentation and promote engineering best practices.
Required Qualifications & Experience
- Strong commercial experience with dbt and Snowflake.
- Proficiency in Python and SQL.
- Hands-on experience with Microsoft Azure services.
- Experience using Fivetran or a comparable managed data-integration platform.
- Practical knowledge of Kubernetes and containerised workloads.
- Strong understanding of Git-based development workflows.
- Experience designing and maintaining automated CI/CD pipelines.
- Good knowledge of dimensional modelling, particularly the Kimball methodology.
- Experience implementing or working with Data Vault models.
- Understanding of data governance, security, lineage, testing, and observability.
- Strong communication, problem-solving, and stakeholder-management skills.
Preferred/Additional Skills
- Snowflake performance tuning and cost optimisation.
- Infrastructure as code, such as Terraform or Bicep.
- Azure DevOps or GitHub Actions.
- Data catalogue and orchestration technologies.
- Working in Agile, cross-functional delivery teams.
What We Offer
- The opportunity to shape and improve a modern cloud data platform.
- Challenging data-engineering projects with meaningful business impact.
- A collaborative environment that values quality, ownership, and continuous improvement.
- Ongoing learning and professional-development opportunities.
- Flexible or hybrid working, subject to business requirements.
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