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# Data Engineer

- **Company:** Advanced Resource Managers
- **Location:** London, UK
- **Salary:** £117,000.0 - £127,400.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Microsoft Azure, C Sharp (Programming Language), Code Review, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Dimensional Modeling, Github, Python (Programming Language), Power BI, Standard Sql, TypeScript, Data Processing, Microsoft Power Automate, Azure Data Factory, GitHub Copilot, ReactJS, Snowflake, Software Version Control, Serverless Computing
- **Published:** August 19, 2026
- **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-E1A5B3DFC11CA26102/

## About the Role

* Strong SQL and Snowflake experience.
 * Data engineering and ETL/ELT development.
 * Dimensional modelling (Kimball methodology).
 * dbt development and engineering best practices.
 * Azure Data Factory, Azure Functions and CI/CD.
 * Python development for automation and data processing.
 * Azure DevOps or GitHub.
 * Experience using AI development tools such as GitHub Copilot or Microsoft Copilot.
 * Financial Services, Asset Management or Wealth Management experience

Desirable Skills

 * .NET/C#
 * React/TypeScript
 * Power BI
 * Advanced Snowflake capabilities (Snowpipe, Streams, Tasks)

## Description

We are seeking a hands-on Software/Data Engineer to join a modern data platform team delivering analytics, reporting and AI-enabled solutions. This role is primarily focused on Snowflake, Azure, Python and CI/CD, with some exposure to .NET/C# and React/TypeScript environments.

The successful candidate will build and support scalable data solutions, contribute to cloud-based platform development and help drive engineering best practice across the team.

Responsibilities

 * Develop and maintain Snowflake data models, transformations and pipelines.
 * Build and enhance dbt models, testing frameworks and deployment processes.
 * Develop Python utilities and services for data integration and automation.
 * Support Azure Data Factory, Azure Functions and CI/CD pipelines.
 * Use Azure DevOps or GitHub for source control, code reviews and deployments.
 * Troubleshoot production issues and improve platform reliability and supportability.
 * Collaborate with engineers, analysts and stakeholders to deliver practical solutions.


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