Jobs at CUBE (cube.global)

Design and own scalable, secure data architectures and pipelines. Translate business needs into technical designs, set standards, guide engineering teams, ensure performance, reliability, security, CI/CD, and maintain architectural documentation across global teams.

Analyzes, cleanses, validates, and enhances customer risk and control data within the CUBE Network. Supports data matching using Python-based tools, collaborates with subject matter experts, and works with Product and Engineering to improve processing workflows. Helps define risk and control indices, automates analysis, and maintains high standards of data quality, consistency, and accuracy.

Leads complex enterprise sales across European financial services markets, originating and closing high-value opportunities with banks and other regulated institutions. Responsibilities include prospecting, discovery, proposals, demonstrations, pricing, forecasting, stakeholder engagement, pipeline development, account planning, renewals, and expansion. The role requires credible risk and compliance expertise, experience selling RegTech or regulatory intelligence solutions, managing C-suite relationships, and closing multiple seven-figure contracts.

Own operational analytics and executive reporting by transforming delivery, quality, content-source, and API data into trusted dashboards and actionable insights. Responsibilities include delivery forecasting, defect and data-quality analysis, source and integration telemetry, ROI and capacity modeling, KPI definition, and reporting cadence management. The role partners with engineering, QA, DevOps, and operations teams to improve data reliability and inform planning, resourcing, and investment decisions.

Own agentic AI products end to end, from customer discovery and AI prototyping through delivery, launch, and iteration. Define product strategy, success metrics, and priorities; collaborate closely with engineering, design, commercial teams, and customers; coordinate go-to-market enablement; analyze usage data and feedback; and use AI and agentic tools to accelerate research, prototyping, and product development.

Drive new business sales for CUBE Intel’s mid-market SaaS solution. Responsibilities include prospecting, territory planning, managing full sales cycles, engaging senior compliance stakeholders, negotiating and closing deals, maintaining CRM discipline, forecasting pipeline, improving conversion rates, and contributing to go-to-market strategy. The role requires proven B2B SaaS sales experience, strong communication and negotiation skills, and the ability to manage complex, multi-stakeholder sales cycles.

Own the full customer relationship from initial engagement through implementation, delivery, and business-as-usual transition. Lead client meetings, workshops, requirements gathering, platform demonstrations, stakeholder management, issue resolution, and service delivery. Collaborate with legal, finance, technology, partners, and offshore teams while advocating for customer needs and influencing the product roadmap. Support UAT, continuous improvement, and regulatory technology implementations for financial services clients.

The Data Quality Analyst profiles data, creates quality rules, monitors dashboards, investigates anomalies, identifies root causes, and performs controlled data corrections. The role improves SSIS/ETL ingestion pipelines, validates production data, documents governance and remediation procedures, and collaborates with technology, product, compliance, and business teams. It also supports AI-enabled monitoring and automation to improve data accuracy, reduce recurring defects, strengthen audit outcomes, and enhance customer-facing services.

Perform quality assurance reviews of regulatory data, meeting accuracy and SLA targets. Analyze datasets to identify errors, inconsistencies, and anomalies; collaborate with Data Quality and governance teams to implement controls, validations, and automated checks. Identify recurring issues, recommend process improvements, support automation initiatives, and improve QA documentation while ensuring compliance with data management policies and regulations.

Own the end-to-end production lifecycle of machine learning models and LLM integrations. Build Azure-based ML pipelines, deployment and serving infrastructure, monitoring, drift detection, rollback systems, experiment tracking, and model governance. Manage LLM providers, gateways, prompt versioning, observability, token usage, and costs. Partner with data scientists and engineers to establish MLOps practices, CI/CD, infrastructure as code, automated testing, reliability, and operational efficiency.

Serve as the single client-facing lead owning end-to-end implementation, stakeholder management, and BAU transition for RegTech SaaS clients. Run workshops, manage project delivery, collaborate with legal/finance/technology teams, perform UAT, and advocate client needs to influence product roadmap while ensuring service quality and retention.

The Senior Customer Success Manager will enhance client relationships, drive product adoption, manage renewals, and ensure customer satisfaction for enterprise financial services clients.

Lead commercial outcomes for CUBE in the US and Eastern Canada, driving new logo acquisition and enterprise expansion. Own NRR targets, manage complex multi-stakeholder sales cycles, negotiate enterprise renewals/expansions, recruit and develop a regional sales team, maintain Salesforce hygiene and forecasting, and collaborate with Customer Success, Solutions Engineering, Product, and Marketing to grow account penetration and market presence.