Top Remote Data & Analytics Jobs in Houston, TX

Build and maintain production-grade dbt data models and pipelines across ingestion, transformation, and visualization. Develop reliable datasets supporting reporting, analysis, finance, revenue recognition, and company decision-making. Collaborate with Finance, Engineering, Sales, Product, and Marketing to understand data needs, improve manual workflows, validate data accuracy, and create scalable solutions using modern data tools.

Build and own analytics for Provider Operations, including funnel, coverage, quality, tiering, retention, forecasting, and rate strategy. Develop dashboards, recurring reports, quality frameworks, and forecasting models that support operational decisions. Partner with Recruiting, Calendar Operations, Product, Engineering, and Data teams to improve tools and instrumentation. Present actionable insights to leadership and drive adoption.

Senior Business Intelligence Analyst who develops and governs Power BI dashboards, analyzes clinic performance metrics, ensures reporting accuracy, and translates operational needs into technical requirements. The role manages BI projects end to end, prioritizes analytics tickets, presents insights to executive stakeholders, establishes reporting standards, contributes to data-model requirements, and mentors junior analysts across clinical and corporate operations.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Designs, builds, tests, maintains, and optimizes large-scale data pipelines, ETL processes, ingestion workflows, and cloud data storage. Develops Databricks data engineering and AI/ML pipelines, Azure Data Lake solutions, Power BI dashboards, and CI/CD automation. Ensures data quality, security, scalability, cost efficiency, and reusable engineering practices while collaborating with distributed technical teams.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Analyzes healthcare claims, provider, pharmacy, and enrollment data to identify trends, improve data quality, optimize workflows, reduce costs, and support business decisions. Translates business needs into requirements, develops complex SQL queries, validates data, recommends process improvements, coordinates projects, and serves as a liaison among operations, research and development, IT, and external partners. Also mentors team members and communicates technical findings to nontechnical stakeholders.

Owns and codifies business definitions and calculation methods for legal spend analytics, audits legacy Excel/PowerPoint artifacts, validates analyses (SQL and AI), supports reporting and storytelling for senior law department and C-suite audiences, and helps migrate analyses into modern analytics tooling.