Top Senior Analytics Jobs in Houston, TX

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and modernization initiatives. Establishes data ownership models, roadmaps, KPIs, and governance frameworks while partnering with executives and business functions. Builds data and analytics capabilities, develops investment cases, drives transformation value realization, promotes data literacy, and leads cross-functional change to improve decision-making and business outcomes.

Leads pricing and analytics strategy, prioritizes analytical requests, translates ambiguous business questions into recommendations, and delivers executive insights. Owns business strategy, product and pricing analytics, credit risk modeling, marketing insights, and cross-functional execution. May manage analysts, oversee projects, develop business requirements, and partner with Sales, Finance, IT, Operations, and other teams to improve profitability and performance.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Leads the enterprise communications measurement program, developing KPI frameworks, benchmarks, reporting products, and analytics roadmaps. Translates communications, marketing, digital, media, social, and campaign data into executive insights and strategic recommendations. Manages analytics technologies and vendors, partners with IT on data governance and quality, advances automation and AI capabilities, and trains stakeholders on measurement practices and reporting tools.

Leads enterprise business intelligence and analytics for Internal Audit, including Power BI dashboards, executive reporting, KPI frameworks, semantic data models, data integration, quality, governance, and advanced analytics. Translates complex data into actionable insights for senior leadership, supports risk and performance analysis, manages stakeholder requirements and delivery priorities, and mentors analytics team members.

Leads HGO’s enterprise analytics engineering initiative, building a Snowflake data warehouse with dbt transformations, modern BI, and AI capabilities. The role manages a growing team, oversees technical implementation partners, translates executive priorities into metrics, and delivers donor, campaign, ticketing, pricing, forecasting, and audience analytics. It also drives business architecture, process modernization, and practical AI adoption while remaining hands-on with data modeling, transformations, testing, documentation, and stakeholder requirements.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Build and govern clinical analytics datasets, SQL transformations, data marts, dashboards, and reporting solutions for clinical quality, patient safety, outcomes, regulatory, and research initiatives. Partner with clinicians, executives, researchers, and enterprise data teams to define metrics, ensure data integrity, implement testing and governance frameworks, and deliver trusted executive, board, regulatory, and clinician-facing insights using modern cloud data platforms.

Leads analytics strategy and delivery by partnering with business stakeholders, customers, and data engineering teams. Defines and prioritizes analytical roadmaps and backlogs, translates business needs into technical requirements, supports data governance, coordinates development, communicates progress, and manages user acceptance testing. The role promotes data-driven decision-making and ensures analytical solutions deliver sustainable business value.

Designs, builds, and optimizes enterprise data pipelines, warehouses, lakes, semantic models, and ETL/ELT solutions. Develops SQL and Power BI solutions, leads data modeling, ensures data quality and governance, resolves performance issues, and contributes to data architecture. Collaborates with HR stakeholders, analysts, data scientists, and technology teams to deliver scalable analytics and reporting platforms.

Build and maintain dbt SQL models, data pipelines, curated datasets, reports, and dashboards supporting state partners, customers, Finance, Operations, and executives. Own external and internal Metabase environments, support the data warehouse, and establish consistent metric definitions across technical and non-technical teams. The role also requires analytics support, stakeholder communication, and experience with Airflow, Python, and Git-based workflows.

Analyze personal loan product performance, customer behavior, funnel conversion, campaigns, and key performance metrics. Design measurement frameworks, identify tracking gaps, conduct root cause analysis, develop A/B tests, support analytics infrastructure, and create dashboards. Partner with Product, Engineering, Data Science, and Business teams to translate insights into product improvements and increased origination volume.

Leads the enterprise business intelligence and analytics strategy, manages BI and data analysts, and oversees analytics roadmaps, projects, platforms, dashboards, and vendor relationships. Translates complex data into actionable financial and business insights, supports SAP and Power BI platform upgrades, manages delivery timelines and resources, and coaches team members. The role also drives stakeholder engagement, continuous improvement, talent development, and data-driven decision-making across the organization.

Own Step’s analytics data models, transformation pipelines, metric definitions, semantic layer, and data quality practices. Partner with Product, Marketing, Engineering, Risk, Growth, and Finance to establish trustworthy data foundations and enable self-service analysis. Build reusable query, visualization, and code components; apply AI-augmented workflows; and collaborate with data scientists, analysts, and platform engineers. The role requires strong SQL, modeling, pipeline, BI, communication, and independent ownership skills, with occasional travel for team onsites.

Owns a six-month analytics engineering engagement covering scalable Snowflake architecture, marketing and sales ingestion, finance automation with LLM agents, data reconciliation, and governed Tableau reporting. Builds production-ready pipelines, data models, quality monitoring, human-in-the-loop controls, and row- and column-level security. Delivers documentation and knowledge transfer while coordinating independently with finance and publishing stakeholders.

Maintains and monitors Azure Databricks data pipelines, troubleshoots data issues, collaborates with stakeholders on data requirements, documents processes, performs backups and disaster recovery drills, and supports data access and usage. The role requires extensive data engineering experience, Azure expertise, incident management knowledge, and strong problem-solving skills.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Build and maintain production data pipelines that transform robot logs and telemetry into reliable, queryable datasets. Design Spark-based ETL workflows, orchestrate processing with Airflow or similar tools, manage gold-layer datasets, and implement data quality, schema evolution, monitoring, and metadata practices. Collaborate with robotics, hardware, reliability, analytics, and ML teams on data modeling, fleet insights, debugging, and root-cause analysis. The role may also contribute to Python, Java, or C++ libraries supporting data capture and consumption.

The Senior Data Analyst partners with business and technical stakeholders to translate business questions into analytical frameworks, KPIs, dashboards, and actionable recommendations. Responsibilities include marketing analytics, customer insights, CDP and Salesforce enablement, data governance, metric standardization, data-quality improvement, SQL-based analytical dataset development, and executive reporting. The role supports enterprise analytics initiatives across marketing, sales, service, data engineering, and technology teams.