Top Remote Analysis Reporting Jobs in San Antonio, TX

Design, build, deploy, and operationalize scalable data engineering solutions for customers. Responsibilities include developing pipelines, transforming and cleansing data, analyzing sources, implementing governance, security, and quality practices, testing data movement and transformation code, resolving defects and incidents, and advising customers on technical decisions. The role also supports AI, machine learning, business intelligence, and data product adoption while collaborating across teams and educating end users.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Own end-to-end analytics across marketing, revenue, product, and partnerships. Build reliable data models and semantic layers in a lakehouse, maintain dashboards and monitoring, investigate anomalies, conduct experimentation, and translate complex analyses into recommendations for senior stakeholders. The role requires advanced SQL, Python, data modeling, stakeholder communication, autonomy, and mentoring, with responsibility for improving data quality and building analytical standards in a high-growth startup.

Monitor news, media, social platforms, and events; prepare data for media analysis and reports; create Excel pivot tables, charts, and visualizations; write analytical insights; support research projects; and validate proprietary reputation-risk and stakeholder-view scoring. The intern will help deliver timely client alerts, briefings, and longer-term reports while collaborating with analysts and interpreting trends across business, culture, and politics.

Design, build, and maintain scalable production data pipelines and cloud-based solutions in Microsoft Azure. Develop Python, SQL, Spark, Spark SQL, and PySpark workflows for data ingestion, transformation, integration, analytics, reporting, and machine learning. Monitor, troubleshoot, validate, and optimize data pipelines and large-scale processing workloads while collaborating with technical teams and stakeholders. Document architectures and follow software engineering best practices for testing, version control, and deployment.

Designs, administers, and optimizes data systems supporting FSA IAM applications. Develops migration plans from legacy AIMS and PAS systems, creates data models, mappings, layouts, dictionaries, and integration processes, and supports analytics and fraud detection. Manages database configuration, performance tuning, monitoring, backups, capacity, secure data handling, encryption, network data flows, token management, and documentation while collaborating with development, security, and operations teams.

Lead test-and-learn initiatives across insurance products and member experiences. Design experiments, analyze incremental impact using statistical and causal methods, integrate complex data sources, build lifetime value models, and translate findings into actionable business recommendations. Partner with product, marketing, operations, and strategy stakeholders while developing dashboards, documentation, and organizational experimentation capabilities.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Lead WEX’s semantic data platform and Data-as-a-Service strategy. Define architecture and roadmap, build trusted semantic business objects and governance capabilities, enable AI and agentic applications, and drive enterprise adoption. Lead engineers, architects, and technical leaders while partnering with Product, AI, Analytics, Risk, Finance, and business teams. Translate complex business concepts into scalable platform abstractions and oversee modernization of large-scale data ecosystems.

Conduct individual and institutional prospect research, donor profiling, pipeline qualification, due diligence, and risk assessments. Synthesize financial, philanthropic, and relationship information into briefings, event snapshots, leadership summaries, and board bios. Proactively identify new donor prospects, monitor wealth and philanthropic trends, and support board and geographic expansion initiatives. Train Development staff on research tools, establish service protocols, and manage research requests independently while protecting confidential information.