Top Senior Data & Analytics Jobs

Analyze product and business data to generate actionable insights, conduct hypothesis-driven investigations and A/B tests, build business intelligence dashboards and alerts, recommend analytics tools, and track lifetime value and cohorts. The role partners with developers, the Head of Growth, and executive leadership to influence product strategy and live operations.

Leads data analysis and semantic modeling for certified data products, builds and rationalizes Power BI dashboards, partners with Finance and business stakeholders on requirements and UAT, and drives report consolidation. The role requires expertise in Power BI semantic modeling, DAX, gateway administration, advanced SQL, Athena, Redshift Spectrum, dimensional and star-schema analytics, and rebate, sales-to-GMR, and inventory domains.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

Designs and maintains pipelines migrating financial data from legacy Oracle databases to Oracle ERP. Develops SQL and PL/SQL transformations, backend integrations, data mappings, reconciliation, testing, monitoring, troubleshooting, and documentation. Partners with accounting, business, and technical stakeholders to resolve issues and support large-scale financial transformation. The role also involves AI tool adoption, code reviews, solution design, deployment activities, governance, communication, mentoring, and project oversight.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Lead hands-on Workday reporting and HR analytics: design, build, and maintain reports, dashboards, calculated fields, and data models. Partner with HR, HRIS, IT, finance, and vendors to translate requirements, improve data quality, ensure secure access, and scale self-service analytics and governance across global HR systems.

Develop and maintain data models, semantic layers, dashboards, and Python- and SQL-based reports for claims analytics. Analyze operational performance, investigate root causes, and provide actionable recommendations to leadership. Collaborate with engineering, operations, and other stakeholders to translate source systems into standardized data models and deliver effective analytical solutions. Communicate findings through clear writing and presentations while helping shape a growing data team.

Analyze AI Search data to identify meaningful questions, build recurring reporting, investigate changes in visibility and model behavior, refine measurement methods, and translate findings into product, customer, and prospect recommendations. Partner with Product and Data teams, create customer-ready analyses and presentations, communicate findings to varied audiences, and document methods and limitations. The role requires strong SQL skills, analytical judgment, and the ability to work with complex datasets.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Manage complex SQL Server and Azure SQL environments, including database architecture, data modeling, ETL, stored procedures, reporting, performance tuning, security, backups, recovery, patching, failover, and production support. Develop SSIS and Azure Data Factory pipelines, optimize queries and indexes, administer permissions and encryption, maintain SSRS and Power BI reporting, document technical solutions, and supervise staff or projects.