Top Remote Data & Analytics Jobs in Houston, TX

Leads the organization’s data strategy, analytics, and measurement capabilities. Advises enterprise clients on attribution, incrementality, marketing mix modeling, customer acquisition, and lifetime value. Develops measurement frameworks, dashboards, reporting products, and analytics tools while partnering with strategy, sales, client services, and AI teams. Builds internal data literacy, coaches talent, supports commercial growth, and represents the company as an external thought leader in partnership marketing measurement.

The Senior eDiscovery Analyst advises litigation teams and clients on ESI preservation, collection, processing, review, analysis, and production. The role manages Relativity applications, develops discovery databases and documentation, troubleshoots data, and supports cloud and collaboration data sources. It designs and validates Relativity aiR workflows, mentors analysts on generative AI, and ensures defensible review practices. The analyst also manages multiple projects, maintains technical expertise, supports clients and vendors, works Eastern Time hours, and meets a 1,400-hour annual billable goal.

Analyze complex datasets to identify trends, patterns, anomalies, and business opportunities. Develop KPIs, perform root-cause analysis, build Power BI dashboards using DAX, SQL, and Power Query, validate data quality, automate reporting, and translate findings into actionable recommendations for business stakeholders.

Design, develop, and maintain enterprise data solutions and pipelines using Azure data platform and Microsoft Fabric. Support data modeling, master data management, medallion architecture, data quality, and integrations to produce trusted, scalable data for analytics and BI.

Collect and analyze carbon credit trade data, verify transactions, and produce daily price assessments. Report breaking and feature news on carbon markets, policies, and market fundamentals. Research regulatory and program developments, publish analysis and social content, and develop industry sources.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

Maintain and secure the church CRM by entering, auditing, deduplicating, and updating constituent records. Build reports, dashboards, mailing lists, and analytics; support online forms, event registrations, and integrations. Train staff, manage user permissions, coordinate with IT/vendors, perform audits, and document procedures to support ministry decision-making and data-driven operations.

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Design, build, and maintain scalable big data pipelines, architectures, distributed databases, and storage systems. Use Python and frameworks such as Hadoop, Spark, or Flink for data integration, transformation, and processing. Ensure system performance, availability, security, governance, and data quality while collaborating with cross-functional teams and documenting technical solutions.