Chabez Tech LLC

Compensation

Full Description

Software Design for Data Systems Design and implement scalable data services and APIs for data consumption Build production-grade data applications using modern software engineering practices Develop microservices for data ingestion, transformation, and serving layers Create robust error handling, retry mechanisms, and monitoring for data systems Outcome: Production-ready data services with 99.9% uptime and comprehensive observability Data Pipeline Development Build and maintain complex ETL/ELT pipelines processing healthcare data at scale Implement real-time streaming data pipelines for time-sensitive healthcare events Design orchestration workflows for dependencies across multiple data systems Optimize data processing jobs for performance and cost efficiency Outcome: Reliable, efficient data pipelines that scale automatically with data volume Technical Leadership Provide technical guidance on software design patterns for data applications Lead code reviews ensuring software engineering best practices in data code Mentor junior engineers on both software development and data engineering concepts Drive adoption of test-driven development and CI/CD for data systems Outcome: High-quality, maintainable codebases with comprehensive test coverage Data Product Engineering Build data products as full-stack applications with APIs, SDKs, and documentation Implement data quality frameworks with automated testing and validation Create self-service data platforms with proper authentication and authorization Develop data catalogs and discovery tools as software products Outcome: Data products that function as reliable, user-friendly software applications Complex Problem-Solving Debug distributed system issues across data pipelines and services Resolve performance bottlenecks in both application code and data processing Implement caching strategies and query optimization for data services Design fault-tolerant systems with proper failover and recovery mechanisms Outcome: Resilient data systems that gracefully handle failures and scale demands Collaboration and Communication Work with software engineers to integrate data services into applications Partner with platform engineers on infrastructure and deployment strategies Collaborate with data scientists to productionize models as services Communicate technical designs and trade-offs to stakeholders Outcome: Seamless integration of data systems with broader application ecosystem Compliance and Security Standards Implement secure coding practices for data applications handling PHI Build data access controls and audit logging into all data services Ensure HIPAA compliance in all data processing and storage systems Maintain security scanning and vulnerability management for data applications Outcome: Secure, compliant data systems that pass all security audits