Data Developer

Rimes provides enterprise data management solutions to the global investment community. Driven by our passion for solving the most complex data problems, we provide our clients with investment intelligence that powers more than US$75 trillion in assets under management annually. The world’s leading institutional investors, asset managers and service providers rely on Rimes to help them make better investment decisions using accurate information and industry-leading technology.

The Data Team at Rimes delivers cloud-based financial datasets that support critical investment decisions for institutional clients globally. 

As a Data Developer, you will design and operate data pipelines on modern cloud platforms, transforming raw vendor data into validated, production-ready datasets. You will contribute to the scalability, reliability, and accuracy of the Rimes data platform, supporting both standardised and client-specific solutions. 

• →Build and maintain scalable data pipelines using Databricks and PySpark to ingest, transform, and deliver financial datasets  
• →Ensure datasets are accurate, consistent, and validated, supporting downstream analytics and reporting  
• →Integrate and manage data from global vendors, adapting to feed changes and evolving data requirements  
• →Translate business and client requirements into robust, production-ready data workflows  
• →Partner with product and client teams to deliver data outputs aligned to agreed timelines and quality standards  
• →Contribute to solutions supporting multiple asset classes and investment workflows  
• →Operate within structured processes and tooling to ensure traceability, control, and operational resilience of data pipelines 

• Strong programming skills in Python and PySpark  
• Hands-on experience working with Databricks or similar distributed data processing platforms  
• Familiarity with version control systems (e.g. Git)  
• Degree in a technical discipline (e.g. Engineering, Computer Science, Mathematics)  
• At least 1 year of experience working with data in a technical or project-based context  
• Experience working with structured or semi-structured data, with an emphasis on data transformation and validation  
• Strong problem-solving skills with a high level of accuracy and attention to detail  
• Able to manage multiple tasks and priorities effectively  
• Clear and effective communication skills  
• Comfortable working independently while collaborating across distributed teams 

• Experience with SQL and data lake / lakehouse architectures  
• Familiarity with data formats such as Parquet, XML, and ingestion via APIs  
• Exposure to platforms such as Snowflake or Foundry (Palantir)  
• Understanding of financial markets or financial datasets  
• Experience using Excel for data analysis or validation  
• Progress toward CFA or equivalent financial qualification