Top Data & Analytics Jobs

The Staff Implementation Engineer will lead complex data integrations, develop big-data pipelines, and mentor engineers, ensuring high standards for data security and governance.

The Staff Quantitative Developer will enhance risk analytics capabilities, develop pricing libraries and risk models, and mentor engineers while working with clients.

Build and maintain business and consumer metrics and curated datasets, improve product data quality, define requirements with analytics engineering, validate and UAT event-based data, and partner cross-functionally to deliver analytics, visualizations, and data-driven insights.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

Partner with Customer Success and CS Ops to build post-sales analytics: customer health scoring, renewal and renewal pipeline reporting, billing and support signal analysis, and expansion/upsell dashboards. Own dashboard ecosystem, translate stakeholder requests into scalable reporting, collaborate with Finance and Data Engineering, and leverage AI tools to accelerate analytic workflows and maintain data quality for retention and expansion decision-making.

Lead design, development, testing, implementation, and support of SAP-based BI/BW and BusinessObjects analytics for Finance. Work with stakeholders to gather requirements, build interactive dashboards (SAP DesignStudio), create specifications, manage testing and training, support production systems, and drive process improvements and small projects.

Lead analytics for lead intelligence and revenue optimization: develop forecasting, modeling, and simulation to prioritize lead inventory, recommend allocation rules, build KPIs, and partner cross-functionally to implement rules and drive revenue outcomes.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Support stability and success of software updates and product launches by partnering with Product and Engineering. Use dashboards and data analysis to monitor KPIs, diagnose root causes, drive escalations, validate launch readiness, enhance agent tools, and lead AI/automation initiatives to improve agent performance and customer experience.