Top Remote Analysis Reporting Jobs in San Antonio, TX

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Build and support scalable big data pipelines, integrations, and Data Lakehouse architecture for marketing, analytics, reporting, and AI applications. The role develops data models, monitors data quality, troubleshoots production issues, provides post-deployment support, and partners with analytics, data science, business, and engineering teams on long-term platform strategy.

Lead paid media analytics for Life Company, using SQL/Python and advanced statistics to measure and optimize paid social/search and AI-powered search. Build audience segmentation, run incrementality/experimentation, create visualizations and recommendations, and partner with marketing to drive acquisition and engagement.

The role involves driving the identification of requirements, improving systems processes, developing prototypes, and ensuring usability in product development projects within an AI company.

Short-term paid project to export your personal financial data from at least seven apps (including five mandatory categories), create two financial artifacts (spreadsheets or trackers), redact PII locally using a provided tool, and submit matching, recent historical datasets for quality review and final approval. Paid per approved dataset; expected completion within the project timeline.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Build and maintain web crawling and scraping pipelines to collect, transform, and deliver third-party healthcare data. Research sources, assess feasibility, implement extraction strategies, test for quality, and maintain scrapers when sources change. Participate in weekly standups and initial fundraising activity.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Designs, develops, and maintains scalable cloud-based data solutions, ELT/ETL pipelines, data warehouses, curated datasets, and transformation logic using Snowflake and related tools. Optimizes SQL and warehouse performance, monitors workflows, supports data governance and quality initiatives, documents data flows, and delivers trusted datasets for Tableau reporting. Collaborates with business and technical stakeholders in Agile processes while ensuring secure handling of sensitive PHI data.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Own end-to-end data engineering for a business domain, including API and other-source ingestion, dbt models, orchestration, data-quality testing, monitoring, documentation, and performance. Build reliable, AI-ready single sources of truth and ensure data freshness, accuracy, traceability, and scalability. Collaborate with stakeholders and the Director of Data, establish engineering patterns, review work, and mentor other engineers.