Top Remote Data & Analytics Jobs in Houston, TX

Lead enterprise data architecture across AWS and Databricks Lakehouse: design scalable data models, ensure governance and data quality, mentor teams, evaluate and adopt data technologies (Delta Lake, Unity Catalog), oversee large projects and deliverables, and incorporate generative AI to accelerate data modeling and delivery.

Owns and leads commercial master data management across HCP, HCO, payer, patient, product, and organizational domains. Establishes governance frameworks, stewardship programs, data quality standards, matching and survivorship rules, and trusted golden records. Manages commercial data platforms, integrations, analytics datasets, releases, vendors, and offshore teams. Writes SQL, builds validations and data pipelines, troubleshoots integrations, supports commercial launches, and drives operational improvements across pharmaceutical commercial systems.

Analyzes claims portfolio data to identify trends, forecast losses and reserves, monitor performance, and explain variances. Develops reporting tools, dashboards, and data models while ensuring data integrity and compliance with claims policies. Partners with Claims, Finance, Actuarial, IT, Operations, and external stakeholders to support portfolio reviews, resolve reporting gaps, improve processes, and provide actionable insights for business decisions.

Support Numerator clients through ad hoc analyses, consumer-panel insights, platform guidance, reporting, and recommendations that improve sales and marketing effectiveness. The role requires understanding syndicated and household panel data, business intelligence platforms, client relationship management, presentations, and data-driven problem solving. It also involves developing expertise in Numerator solutions and sharing consumer behavior findings through industry content, forums, whitepapers, and blogs.

Performs geospatial data management, analysis, visualization, and analytical modeling for government and commercial clients. Supports hazard identification, risk assessment, and risk reduction efforts using ArcGIS and Microsoft tools. Develops web, mobile, and desktop applications; tests, deploys, documents, and maintains solutions. This non-full-time, on-call role requires frequent travel and deployment to disaster recovery sites nationwide.

Lead the architecture and scaling of Overstory’s data platform for AI-powered vegetation analysis. Design and operate large-scale geospatial and temporal data pipelines, orchestration systems, event-driven workflows, service-oriented architecture, data quality frameworks, and observability practices. Drive architectural standards, system design, scalability, reliability, and traceability while mentoring engineers and collaborating with data, ML, and product teams.

Own production data ingestion pipelines for healthcare and benefits data, including normalization, mapping, validation, reconciliation, observability, and secure handling of sensitive information. Unify census data processes, scale the platform, improve identity matching, and build automation and TypeScript tooling. The role requires strong Python and SQL skills, production orchestration experience, reliable testing and data-quality practices, and effective communication with technical and nontechnical stakeholders.

Manage end-to-end data operations, including collection, processing, delivery, pipeline optimization, and data quality monitoring. Collaborate with engineering, product, and operations teams to improve data workflows, identify inefficiencies, and implement scalable solutions. Analyze data to provide actionable insights for decision-making and AI model development while communicating technical issues to non-technical stakeholders.

Designs, develops, and maintains scalable ETL pipelines, data lakes, warehouses, and integrated data solutions. The role includes requirements analysis, Agile collaboration, testing, debugging, documentation, cloud data engineering, and optimization of reliable and performant systems. It requires strong Python, SQL, database, distributed processing, data engineering, software development, and cloud platform skills, along with effective communication and problem-solving abilities.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.