Top Senior Data & Analytics Jobs in San Antonio, 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.

Build and support scalable big data pipelines, integrations, and Data Lakehouse architecture for marketing, analytics, reporting, and AI applications. Develop data models, monitor data quality, troubleshoot production issues, and provide post-deployment support. Collaborate with analytics, data science, AI, business, and engineering teams to improve data accessibility and define long-term platform architecture. The role requires strong Python and PySpark expertise, cloud and distributed-systems experience, and familiarity with orchestration, data governance, and CI/CD tools.

Leads business and data analytics strategy across information management, governance, reporting, analytics delivery, and data platforms. Oversees strategic initiatives, data modernization, reporting optimization, risk controls, and cross-functional teams. Provides executive-level insights, guides architecture and technology decisions, manages priorities and capacity, and drives data-informed business outcomes. Requires substantial analytics experience in financial services, people leadership, large-scale data analysis, Agile project leadership, and strong executive communication.

Develops reporting, forecasting, financial and contract analyses, sales analytics, and profitability insights for the Fuels Value Chain. Partners with field personnel, management, IT, pricing, supply, finance, and other stakeholders to support strategic decisions, business development, CRM requests, process improvements, and commercial value enhancement. Monitors industry and market trends to inform recommendations and marketing strategies.

Develops and maintains production data pipelines, ETL/ELT workflows, data solutions, and ML infrastructure using Python, AWS, and related technologies. Responsibilities include data ingestion, transformation, validation, storage, monitoring, troubleshooting, performance optimization, and deployment. Collaborates with data scientists, analysts, product teams, and stakeholders in an agile environment.

Analyzes complex data from diverse sources to evaluate programs, develop metrics, create datasets and dashboards, conduct statistical and qualitative research, and deliver recurring reports. Presents findings to stakeholders, supports operational decision-making, audits data quality, and collaborates across teams. The role also mentors junior analysts and manages reporting deliverables. Advanced experience with statistical analysis and visualization tools is required, with bioinformatics and multiomics experience preferred.

Designs and governs enterprise data architecture for a banking organization. Responsibilities include developing data migration and streaming strategies, creating data inventories, maintaining architecture documentation, building data models for databases and AI/ML applications, establishing modeling standards, communicating architecture strategies, and coaching staff. Requires extensive experience with data management, data warehouses, ETL, streaming, cloud concepts, architecture, integration, and data platform technologies.

Build and operate Grassroots Carbon’s unified data platform, including AWS-based storage, production ingestion pipelines, scheduled datasets, integrations, model deployment, monitoring, security, and access controls. Migrate and reconcile historical PastureMap data while establishing lineage, shared identifiers, validation, and reproducible workflows. Partner with science, product, backend engineering, and operations teams to productionize models and deliver reliable data services supporting soil carbon modeling, grazing management, and rancher-facing products.

Leads enterprise data architecture for a secure Databricks lakehouse, including Unity Catalog governance, canonical HR data models, DataOps, ingestion, orchestration, APIs, migration, metadata, lineage, quality, and data-product standards. Serves as deputy data workstream lead, guides architecture decisions, reviews technical deliverables, communicates tradeoffs, mentors architects and engineers, and provides technical quality assurance.

Establishes and operates North America Operations’ data-governance framework, including ownership, stewardship, quality, metadata, lineage, definitions, and AI governance. Partners with business, data, technology, risk, and compliance teams to resolve data issues, automate controls, improve trust, and embed governance into data products, analytics, and AI solutions. Develops playbooks, training, metrics, and continuous-improvement processes while driving accountability across functions.