Data Engineer

Pleiad Group; City Of London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Flexible/hybrid working

Job summary

Pleiad Group is seeking an experienced Data Engineer to design, build, and maintain scalable cloud-based data platforms that support reporting, insight, and decision-making. You will work with analytics, engineering, and business teams to deliver trusted, well-modelled data.

You will develop ELT pipelines, implement data models, and optimise Snowflake structures while leveraging Kubernetes, Terraform, and CI/CD practices in a hybrid work setting across the UK.

Qualifications

• Extensive experience with dbt and Snowflake in commercial settings.
• Strong Python and SQL skills for data processing and pipeline development.
• Hands-on use of Microsoft Azure services in data platform projects.
• Experience with Fivetran or similar managed data integration tools.
• Kubernetes and containerised workloads in production.
• Git-based development workflows and code reviews.
• Experience designing automated CI/CD pipelines for data platforms.
• Knowledge of dimensional modelling using Kimball methods.
• Experience with Data Vault models and governance concepts.

Responsibilities

• Build and maintain reliable ELT pipelines using Fivetran, Snowflake, and dbt.
• Develop reusable, tested data models following Kimball and Data Vault principles.
• Write high-quality Python code for data processing, automation, and integration.
• Design and optimize 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.

Skills

dbt

Snowflake

Python

SQL

Microsoft Azure

Fivetran

Kubernetes

Git

CI/CD

Kimball modelling

Data Vault

Data governance

Tools

Terraform

Azure DevOps

GitHub Actions

Job description

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.