Top Data & Analytics Jobs

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.

As a Senior Quantitative Researcher, you will enhance pricing models and algorithms using advanced statistical and machine learning techniques in the fixed income market sector.

The Data Engineering Manager will lead a team in enhancing data delivery and quality, oversee data visualization efforts, manage projects, and partner with business leaders to implement a strategic plan.

Manage research intake and workflows in Jira, enforce sharing and archival standards in SharePoint/Research Hub, leverage AI for tagging and discoverability, prevent redundant research, produce quarterly insight digests, standardize naming and folder structures, and support quantitative and qualitative analysis while managing budgets and vendors.

Partner with Account Management to deliver data-driven planning, whitespace and pipeline models, revenue and budget reporting, rep-level analytics, and forecast improvements. Validate Salesforce data, reconcile budgets and forecasts, measure campaign and pipeline outcomes, and provide executive-ready insights and budget recommendations to improve deal outcomes and guide resource allocation.

The Data & AI Engineer III will lead cloud data engineering solutions, develop data infrastructure, establish architectures, mentor team members, and secure data around cloud systems.

As a Senior Business Intelligence Engineer, you will design and maintain reporting solutions, architect ETL pipelines, and implement AI use cases while collaborating with stakeholders across various business units.

The Analytics Engineer develops data models and KPIs, ensuring data reliability for decision-making while collaborating across multiple departments at Crexi.

Lead data management and governance initiatives: define standards, policies, and lifecycle practices; drive data quality, stewardship, compliance and MDM efforts; develop training and data models; and advise on risk mitigation and operational improvements across the organization.

Lead client-facing analytics engagements during new community deployments. Scope technical requirements, build and maintain secure bi-directional data pipelines, and develop custom analyses, data models, and dashboards to deliver measurable client value within the first 3–6 months. Coordinate between clients, operations, and data architecture teams; travel up to 25% for on-site work.