Teams at Rimes Technologies

Inspect and profile new financial datasets, build and test conceptual/logical/physical data models, document field definitions and relationships, collaborate with Data Engineering to produce ETL/ELT-ready schemas, and maintain model alignment and data quality.

Design, build and operate scalable Databricks/PySpark data pipelines to ingest, transform and validate financial vendor data into production-ready datasets, partnering with product and client teams to meet quality and timeline requirements.

Serve as the client-facing owner of service delivery for financial data products: monitor feeds, troubleshoot issues, resolve client queries and escalations, manage KPIs, run trainings/demos, document processes, and support product use to ensure high-quality client outcomes.