Rimes Technologies - Data Modelling Engineer
Requirements
• 5+ years of experience in data modelling, with a track record of designing conceptual, logical and physical models for production platforms. • Solid grasp of relational and dimensional modelling fundamentals, including hierarchies and history handling (e.g. slowly changing dimensions) • Strong SQL and hands-on experience profiling and validating unfamiliar datasets. • Hands-on experience with Databricks, including Delta Lake and Unity Catalog. • Python for data profiling and validation. • Experience with Git or similar version control systems. • Degree in a technical discipline (e.g. Engineering, Computer Science, Mathematics) or equivalent experience demonstrating strong analytical and data modelling capability. • Strong attention to detail and ability to investigate datasets independently. • Clear communication skills and comfort working with cross‑functional teams. • Organized, proactive, and committed to accuracy and continuous improvement. • Experience working with financial data, including research datasets (e.g. ESG data), with the ability to model data for analytical and investment use cases. • PySpark for data exploration, prototyping or building transformations. • Familiarity with common data exchange and schema formats, such as XML and JSON. • Experience with modern data platforms such as Palantir Foundry or Snowflake. • Strong Excel skills for exploratory data assessment. • Progress toward the CFA or a similar investment qualification, or equivalent knowledge of investment data and concepts
Responsibilities
• Design and maintain scalable data models (tables, relationships, hierarchies, history handling) on Databricks using Delta Lake and Lakehouse architecture. • Profile new index, pricing, reference, ESG, and research datasets to understand structure, fields, data types, keys and vendor specific quirks. • Identify inconsistencies, missing fields, formatting issues, or schema gaps and collaborate on remediation. • Define source-to-target mappings, schemas and handling rules that Data Engineering can implement in ETL/ELT pipelines, and work closely with them to ensure the build matches the design. • Test sample data against models to validate mappings and assumptions before they go into production. • Use Unity Catalog to support governance, lineage and traceability of modelled data. • Document field definitions, data relationships, and handling rules clearly for internal teams, and contribute to modelling standards and good data practice. • Review provider schema updates and adjust models when needed to maintain alignment.
Benefits
• Private Health Insurance (plus eligible dependents) • 23 days of annual leave • Employee Assistance Programme • Compensation: Competitive pay and bonus eligibility • Work Life Balance: Flexible hybrid work environment • Only selected candidates will be contacted for interviews. We appreciate your understanding. Thank you for considering a career with us. • Rimes is committed to promote the values of diversity and inclusion throughout the business. Whether it’s through recruitment, retention, career progression or training and development, we are committed to improving opportunities for people regardless of their background or circumstances. • Visit our Careers page to see our complete listings.
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