Top Senior Data & Analytics Jobs in Houston, TX

Design and develop data pipelines, integrations, transformations, and infrastructure across AWS, Snowflake, Airflow, and MySQL. Troubleshoot warehouse issues, validate data quality, improve pipeline reliability, and translate business needs into data engineering solutions. Interpret technical findings for client recommendations, manage workstreams, review junior team members’ work, and provide technical guidance across managed services engagements.

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.

Leads development of secure, scalable data platforms for KYC and risk assessment. Designs and delivers enterprise data applications, frameworks, APIs, and processing systems; mentors engineers; drives AI-assisted development practices; and ensures secure, reliable, and compliant engineering workflows. The role uses cloud-native technologies, large-scale data processing, databases, observability, orchestration, modern data platforms, and emerging LLM infrastructure while communicating with senior leaders.

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.

Leads data projects from requirements through release, building Python and SQL pipelines, integrating and validating market data, automating processes, and supporting daily price assessments. Reviews code and data quality, develops assessment algorithms, resolves operational issues, and mentors analysts. Acts as a bridge between Data and Index teams while applying commodity market knowledge and AI coding tools to improve team productivity and reliability.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Leads a business intelligence engineering team by setting technical strategy, managing hiring and performance, coordinating sprints and capacity, conducting design reviews, and partnering with stakeholders and peer managers. Oversees data warehouse, BI tooling, and workflow strategy while contributing limited hands-on development, debugging, and fixes. Requires expertise in BI tools, SQL, cloud data warehouses, analytical solutions, and technical team management.

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.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and data modernization. Partners with executives and cross-functional leaders to establish data ownership, improve quality, develop analytics and KPI frameworks, prioritize AI use cases, and measure transformation value. Builds data-focused organizational capabilities, drives adoption and data literacy, develops investment cases, and guides enterprise initiatives that improve forecasting, planning, operational decisions, and business outcomes.

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.