Top Data & Analytics Jobs

Lead the end-to-end migration of quote-to-cash data from Salesforce CPQ and NetSuite into Salesforce Revenue Cloud Advanced and Oracle. Define migration architecture, design ETL pipelines, map and transform complex commercial and financial data, manage cleansing and reconciliation, optimize bulk loads, and lead distributed ETL developers. Produce migration specifications, runbooks, cutover plans, and audit-ready reconciliation reports while coordinating with Finance, Sales Operations, IT, and executive stakeholders.

Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Leads commercial real estate research, analytics, forecasting, risk analysis, and market intelligence using diverse economic, financial, lending, and real estate data. Oversees research tools, models, databases, and quality processes; communicates findings through reports, presentations, webinars, podcasts, and client materials. Mentors team members, partners with Client Services, and standardizes analytical and reporting practices across the Research Group.

Leads the design and implementation of scalable data models, pipelines, and analytics systems. Collaborates with data scientists, product analysts, software engineers, and stakeholders on cross-functional initiatives. Ensures data quality, testing, validation, observability, security, and system reliability while using AI to improve analytical engineering workflows and automate routine tasks.

Administer and optimize IBM Db2 for z/OS production databases, including design, performance tuning, security, backup and recovery, utilities, upgrades, and disaster recovery. Support SQL Server, Azure SQL Managed Instance, data movement pipelines, DDF/DRDA connectivity, and ITIL operations. Maintain documentation, runbooks, audit support, and recovery procedures while mentoring developers and cross-training backup administrators. Participate in on-call rotations and collaborate across mainframe, data engineering, warehouse, application, and systems programming teams.

Leads enterprise data strategy, lakehouse delivery, data products, and data and AI governance. Establishes platform standards, data ownership, quality, lineage, lifecycle, privacy, and regulatory controls. Builds governance operating models for AI development and monitoring, manages platform teams and partners, oversees external data acquisition, and reports risk, maturity, and compliance to executives, clients, and auditors.

Maintain and optimize Oracle databases supporting federal Web/Oracle systems in AWS. Responsibilities include database configuration, performance monitoring, backups and restoration, replication, schema management, release and testing support, firewall coordination, STIG compliance, audit support, and developing infrastructure-as-code solutions. The role requires Oracle DBA, PL/SQL, AWS RDS, database replication, and security compliance experience, along with a Secret clearance and Security+ CE or CCNA Security certification.

Summer data and analytics intern supporting data management, business analytics, machine learning, research, database and spreadsheet maintenance, and technical or operational projects. The intern collaborates with experienced analytics professionals, gathers data, contributes to team initiatives, completes training, and presents program learnings. The role requires strong communication, organization, problem-solving, adaptability, and proficiency with office, Google, Oracle, and other computerized tools.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.