Top Data & Analytics Jobs

Owns the analytics database, data pipelines, modeling, operational reporting, data dictionary, KPI definitions, and scheduled-job operations. Integrates vendor APIs, builds reliable incremental pipelines, creates governed reusable data assets, supports BI users, and leads one analyst. The role also contributes to the analytics roadmap and delivers new data sources and shared business definitions.

Analyzes and maintains customer, item, and configuration master data using Oracle and Microsoft tools. Organizes and validates files for electronic updates, investigates data and process issues, evaluates business impacts, prepares reports, and supports cross-functional projects. Collaborates with business teams to ensure data integrity, accurate national coding, efficient processes, and customer-focused solutions.

Analyzes financial, operational, sales, and customer data for the CEO and executive leadership team. Reconciles inconsistent data sources, builds models, explains performance drivers, and delivers actionable recommendations through board-quality reports and presentations. Leads cross-functional CEO initiatives, supports acquisitions and integration, manages executive reporting, and provides continuity for executive office operations. Handles confidential information and contributes to future analytics and reporting architecture.

Administers and supports Slate CRM environments for undergraduate, graduate, and certificate enrollment operations. Monitors data movement across Slate, Axiom Elite, Ellucian Banner, and third-party integrations; investigates errors, anomalies, fraud, and data-quality issues; and performs reconciliation using SQL, Tableau, and reporting tools. Develops or recommends improvements to validation controls, integrations, and automated monitoring. Provides technical support, translates business requirements, protects confidential records under FERPA, and collaborates with university stakeholders.

Develop and maintain database systems supporting marketing campaigns, including production scripts, tables, stored procedures, views, functions, ETL feeds, data warehouse metadata, automated reporting, and quality-control processes. Prepare campaign universes, selections, suppressions, and creative assignments. Perform code and data audits, troubleshoot production processes, document workflows, and identify process improvements while translating business requirements into executable technical solutions.

Leads enterprise business intelligence strategy, roadmap, governance, analytics, data engineering, data science, and AI-enabled automation. Partners with executives across functions to define KPIs, deliver dashboards and predictive insights, oversee data platforms and integrations, manage technology vendors and budgets, and lead a global team of BI engineers, data engineers, analysts, and data scientists.

Develop and maintain logical and physical data models, architectures, schemas, pipelines, and ETL processes. Ensure data governance, compliance, integration, reuse, and quality. Analyze data requirements, create decision-support materials, and brief senior leaders. The role requires extensive experience in data engineering, ORSA, data science, warehousing, ingestion, profiling, SQL, pandas, Python, and distributed data environments, along with an active TS/SCI clearance.

Leads marketing measurement, forecasting, attribution, media mix modeling, and LTV/CAC analysis across D2C channels. Builds analytical infrastructure, evaluates channel performance, supports budget allocation, and conducts cohort and retention analysis. Partners with executives, marketing, finance, product, and data engineering to translate complex findings into actionable recommendations. The role also establishes reporting for new channels, supports scenario planning, and communicates insights that guide growth and investment decisions.

Build and maintain dbt data models and BigQuery analyses supporting supply, marketplace, and partner success operations. Investigate data anomalies, create dashboards and reporting, improve fill-rate and fulfillment performance, maintain reliable data infrastructure, and eventually develop predictive models. Collaborate with Supply, Marketplace, Partner Success, Product, and Engineering teams to translate business needs into scalable data solutions.

Analyzes business processes, operational metrics, financials, and system requirements to identify trends, resolve problems, and recommend improvements. Partners with management and cross-functional teams to implement process changes, ERP and forecasting solutions, Lean Manufacturing practices, training, and sustainable operational improvements affecting production, materials, and logistics.