Top Senior Analytics Jobs in San Antonio, TX

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Manages reporting and analytics operations, teams, workflows, critical business intelligence reports, and performance metrics. Leads data process improvements, requirements analysis, systems development, testing, reporting projects, and process re-engineering. Uses SQL, data warehouses, QlikView, Tableau, and related tools to support operational, financial, quality, compliance, and strategic decisions. Mentors staff, manages priorities, monitors risks, and partners with business leaders and clients.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

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.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead process mapping, analysis, and redesign to improve efficiency and outcomes. Partner with stakeholders to gather requirements, analyze data (SQL, Excel, Power BI), define KPIs, apply Lean/Six Sigma methods, and support automation and digital transformation initiatives to drive growth, profitability, and loss reduction.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Own the end-to-end analytics function embedded in a business unit (growth, product, AI/automation, or partnerships). Define problems and metrics, build reports and experiments, surface insights, recommend actions, and drive outcomes with cross-functional partners.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Embed with a core business area to define problems, build reports and experiments, analyze data, surface insights, and drive high-impact recommendations end-to-end across growth, product, AI, or partnerships.

Lead analytics for quality and HEDIS performance improvement: design and build reporting, track HEDIS rates and interventions, conduct statistical analysis and predictive modeling, manage data warehouse changes, support audits and special projects, and train stakeholders on analytic solutions.

Lead supply-and-demand forecasting for the psychiatry service line: build and maintain S&D models, integrate models into core data infrastructure, define operational metrics (capacity, clinician utilization, hiring targets), run forecast vs. actual audits, and partner cross-functionally to guide hiring, resource allocation, and operational improvements.