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Data Developers at Rimes build and maintain tools to ingest, validate, and load data from a wide range of global sources into the Rimes platform. They are expected to be knowledgeable about global financial market data, contribute to custom client solutions and work closely with teams across time zones. Rimes’ hand-off management style encourages initiative, problem-solving, and end-to-end ownership of data workflows.
Job Responsibility:
Design, build, and maintain ETL data pipelines to ingest and transform financial datasets
Work with a wide range of structured and semi-structured data, ensuring accuracy and consistency through validation and transformation
Collaborate with 300+ data vendors to integrate new sources and manage feed changes
Translate client and business needs into data workflows, for custom analytics and reporting
Partner with product and client teams to deliver high-quality data outputs on schedule
Build solutions supporting diverse financial asset classes and critical investment systems
Use internal tools and systems to manage data workflows and collaborate across teams
Requirements:
Excellent programming skills in Python
Experience with Git or similar version control systems
Bachelor’s or Master’s degree in science, engineering, or a related technical field
At least 1 year of related work or project experience in a technical, data-driven role
Results-driven and detail-oriented with strong problem-solving skills
Flexible and efficient at multitasking across various assignments
Strong verbal and written communication skills in English
Able to work independently, take initiative, and prioritize effectively
Interested in technology while recognizing the importance of process and structure
Attentive to detail with a demonstrated ability to think creatively
A confident communicator with exceptional interpersonal skills
Nice to have:
Knowledge of SQL, XML, or working with REST APIs
Familiarity with Databricks, Foundry (Palantir), Snowflake, or Parquet files
Solid programming skills in Perl
Understanding of financial markets and financial datasets
Experience working with Microsoft Excel in a data analysis or reporting context
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