Top Senior Analytics Jobs in Houston, TX

Lead embedded analytics for a core business area (growth, product, AI, or partnerships). Define problems, build metrics, run analyses and experiments, deliver insights and recommendations, and drive outcomes end-to-end with stakeholders.

Lead embedded BizOps analytics for a core business area (growth, product, AI, or partnerships). Define questions and metrics, build reports and experiments, surface insights, make data-driven recommendations, and drive cross-functional execution to impact key business metrics and scale the company.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Design, build, and maintain advanced Workday reports, dashboards, and analytics to inform workforce planning and talent strategy. Partner with HR, HRIS, IT, and business leaders to define metrics, validate and govern data, perform deep-dive analyses, support Prism integrations, and deliver executive-ready insights, documentation, and training to enable data-driven HR decisions.

Lead measurement and insights strategies across B2B client programs. Analyze earned/social/web data, conduct secondary research, build measurement frameworks and dashboards, deliver client-facing recommendations, mentor junior staff, and advance agency analytics capabilities.

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 revenue operations and business insights by owning GTM and revenue data integrity. Build reporting and AI-driven insights, run billable usage analysis, manage data flows with Fivetran/Salesforce/Sigma, investigate billing disputes, and translate data into actionable narratives for leadership.

The Director, Analytics Infrastructure & Pipeline Operations is responsible for creating automated data pipelines and centralized feature stores for data science, leveraging AI technologies to optimize workflows and ensure data quality.

Lead implementations and analytics for community health centers: run stakeholder meetings, extract/clean/analyze EHR data, write SQL, build reports and visualizations, provide consultative support and training, manage data initiatives, and recommend product improvements.

Lead implementations and ongoing analytics consulting for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train client data teams, and inform product improvements based on customer feedback and domain expertise.

Lead implementations and provide consultative analytics for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train health center teams, and inform product improvements based on customer feedback and domain expertise.

Manage underwriting analytics, collaborate with cross-functional teams, drive operational improvements, and enhance training for underwriters.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

Lead the Sales Strategy & Analytics function to deliver reporting, KPI tracking, profitability and competitive analysis, and sales technology ownership. Partner cross-functionally to provide executive insights, optimize tools and processes, drive adoption, and develop a high-performing analytics team that improves sales productivity, profitability, and strategic decision-making.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Design, build, and maintain scalable dbt transformation pipelines and dimensional data models on Databricks. Partner with data engineering and stakeholders to deliver trusted silver/gold datasets, implement data quality tests and monitoring, enable self-service semantic layers, and enhance LLM-driven tooling to accelerate analytics and automation.

Lead HR analytics for People & Culture and Capacity & Resource Management: build and maintain dashboards and reports, extract/clean large datasets, deliver talent and capacity insights, run data-driven programs, improve reporting processes, maintain documentation, and mentor team members while collaborating across functions to inform strategic workforce decisions.

Lead end-to-end product analytics for New Content Experiences, partnering with Product, Design, Data Science, and Engineering to analyze large datasets, build tools, ensure data quality, and inform product strategy and decision frameworks.

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.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

Perform financial due diligence data analytics for middle-market M&A: obtain, validate, normalize, analyze transaction data (revenue, costs, inventory), produce dashboards and visualizations, identify trends/outliers, and communicate insights to deal teams and clients.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.