Top Remote Data & Analytics Jobs in San Antonio, TX

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

Design, develop, and maintain conceptual, logical, and physical data models for VHA VFMP modernization. Produce ER diagrams, data dictionaries, and metadata; translate business requirements into scalable database designs; support migration, data governance, security, testing, and collaboration with architects, developers, EDI teams, and IPTs to ensure high-volume, interoperable, and maintainable enterprise data solutions.

The Data Scientist will analyze data to optimize products, drive business decisions, develop models and algorithms, and enhance customer experiences.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

Design, build, and maintain scalable data lakehouse platforms and ELT pipelines. Improve engineering practices, develop automation/tooling, monitor performance, reduce costs, and support platform modernization across Azure and cloud data technologies.

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.