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Sell Rimes' enterprise investment data SaaS: prospect and qualify new logos, expand accounts, coordinate enterprise deal execution, prepare client materials, maintain CRM hygiene, and report pipeline and forecasts.

Prospect and qualify new-logo opportunities, grow and support existing accounts, coordinate enterprise deal execution, create client-facing materials, and maintain CRM hygiene and sales reporting to meet quota.

Lead end-to-end change management for product, platform and operational transformations. Design change strategy, impact and readiness assessments, stakeholder engagement, training and enablement, go-live and hypercare coordination, resource planning, communications, and measurement to embed adoption across global teams and client-facing operations.

The Graduate Analyst role involves supporting client services, performing data quality checks, and assisting in financial analysis, while undergoing an 8-month training across multiple teams.

The Enterprise Sales Engineer partners with sales to lead the technical sales process, engage with clients, design solutions, and deliver compelling product demonstrations, focusing on investment data management and analytics.

Own a portfolio of 4-8 strategic North American enterprise accounts, driving retention, renewals, and expansion. Build C-suite relationships, lead business reviews, manage pipeline and forecasts in Salesforce and Clari, surface client feedback to Product and Services, and apply AI-assisted insights to strengthen account strategy.

Senior pre-sales role owning end-to-end technical sales for enterprise investment data managed services and analytics. Lead discovery, design enterprise data architectures, deliver tailored demos and proof-of-concepts, shape RFP/RFI narratives, and ensure smooth handover to delivery while advising C-suite and investment data stakeholders across Asia‑Pacific.

Support EDM change and onboarding delivery for clients: follow change governance, complete impact assessments, maintain runbooks, triage low-to-mid complexity changes, assist RCAs and client communications, and develop technical skills (including Python and Rimes tools) while transitioning changes into BAU operations.

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.