Top Remote Data & Analytics Jobs in San Antonio, TX

Build and maintain data lakes, data warehouses, and modern data pipelines for a multi-tenant SaaS platform. Design end-to-end data processes, write pipeline and infrastructure code, conduct design reviews, optimize performance, monitor systems, support data governance, and troubleshoot scalability and security issues. Collaborate with technical and business stakeholders, mentor junior engineers, evaluate technologies, document platform architecture, automate testing, and participate in on-call rotation.

Own the architecture, roadmap, and operation of Clarium’s AWS-based data platform. Build reliable batch and near-real-time pipelines, model healthcare supply chain data, optimize Postgres and Snowflake performance, and establish standards for testing, deployment, quality, and governance. Partner cross-functionally to create durable data models, lead multi-quarter initiatives, manage sensitive data controls, and mentor engineers.

Leads and mentors the Data Engineering team while remaining hands-on in designing, building, and maintaining scalable data pipelines, warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical delivery; and resolves complex issues. Partners with Finance and business stakeholders to translate data needs into practical solutions, sets technical direction, evaluates technologies, and communicates strategy, risks, and recommendations to leadership.

Leads and delivers complex data engineering projects, designing scalable data infrastructure, pipelines, warehouses, and data quality solutions. Recommends tools and architectures, optimizes data movement and performance, collaborates across technical teams, mentors engineers, and translates technical concepts for clients and nontechnical stakeholders. The role may also involve real-time processing, data modeling, transformation, security, and MLOps.

Monitor prediction markets and perpetual futures by tracking news, trader sentiment, venues, volumes, open interest, funding rates, and market share. Research protocols and users, build dashboards and datasets, identify product opportunities for Pyth, size opportunities with market and on-chain data, and collaborate with product, engineering, and business development teams. Write research reports, present recommendations to leadership, and evaluate launched initiatives against their original theses.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Build and maintain SQL-based marketing analytics infrastructure, data models, dashboards, and reporting. Analyze marketing channels, affiliates, conversion funnels, cohorts, revenue, profitability, and partner performance. Translate complex findings into actionable recommendations for budget allocation and optimization. Ensure data quality, governance, documentation, and metric consistency while partnering cross-functionally with Marketing, Sales, Finance, Operations, Product, and Technology. The role is a hands-on individual contributor with potential responsibility for mentoring or managing one analyst.

Leads analytics, data architecture, outcomes measurement, health economics and outcomes research, ROI modeling, governance, and client reporting. Manages a multidisciplinary data team and partners with Engineering, Product, executives, and payer stakeholders to translate clinical and financial evidence into actionable decisions. Oversees accurate, repeatable analyses and communicates findings through dashboards, white papers, presentations, and impact briefs.