Top Remote Data & Analytics Jobs in San Antonio, TX

Supports Texas Workforce Commission technology initiatives through business and systems analysis. Documents functional, technical, accessibility, and security requirements; develops user stories, process maps, conceptual and object models, use cases, and architecture diagrams. Creates and executes test cases, ensures requirements traceability, supports legacy-system interfaces, facilitates cross-functional workshops, and assists with project lifecycle artifacts.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Designs, builds, and maintains scalable data pipelines, data models, and platform infrastructure supporting enterprise reporting, analytics, and AI-driven decisions. Responsibilities include ingesting SaaS application data, developing medallion architecture layers and dbt transformations, implementing data quality monitoring, enforcing governance and access controls, and delivering reusable semantic data assets. The role collaborates with analytics, BI, and business teams, participates in Agile delivery, evaluates modern data-stack tools, and promotes engineering excellence through testing, documentation, and code reviews.

Design, build, and operate scalable cloud-native data pipelines and data lake/fabric architectures for Revenue Cycle Management. Implement ETL/ELT, integrate structured and unstructured sources and APIs, ensure data quality, lineage, and governance, and support AI/ML and analytics workloads with CI/CD and DevOps practices.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Design, build, and maintain scalable data pipelines, data models, and analytics solutions using Microsoft Fabric and Azure. Develop Lakehouse and Warehouse architectures, Fabric Notebooks with PySpark and Spark SQL, ETL/ELT workflows, and Power BI semantic models. Optimize performance, ensure data quality, security, governance, and regulatory compliance, and collaborate with analysts, data scientists, and business stakeholders to support business intelligence and advanced analytics.

Administers Informix, MySQL, and other databases across cloud and hybrid environments. Responsibilities include configuration, maintenance, performance tuning, security remediation, replication, monitoring, Tier 3 support, schema changes, migrations, SQL data extraction, backup recovery testing, automation, compliance, and collaboration with engineering, architecture, security, and application teams.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Build and maintain Databricks data pipelines across bronze, silver, and gold layers. Ingest APIs, logs, billing exports, and reference data; implement attribution logic, governance, data quality monitoring, and cost optimization. Manage Unity Catalog permissions, lineage, refresh schedules, incremental processing, and CI/CD workflows while supporting multi-cloud storage and high-volume caller-identity data.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.