Data Engineer

• Own data pipelines, including automated replication and ingestion into the warehouse
• Monitor performance, troubleshoot failures, handle schema changes, and add new data sources
• Maintain and evolve cloud warehouse architecture
• Define layering, naming conventions, performance standards, and cost-efficiency practices
• Ensure scalability across multiple subsidiaries
• Design and maintain dimensional models, including facts and dimensions
• Partner with Finance, HR, and Operations leaders to translate business needs into data structures
• Build models supporting accurate, decision-ready reporting
• Implement testing, documentation, and data quality checks
• Maintain clear data lineage and transparency
• Ensure stakeholders trust reporting accuracy

Senior Data Engineer

• Own data pipelines, including automated replication and ingestion into the warehouse
• Monitor pipeline performance, troubleshoot failures, handle schema changes, and add new data sources
• Maintain and evolve cloud warehouse architecture
• Define layering, naming conventions, performance standards, and cost-efficiency practices
• Ensure scalability across multiple subsidiaries
• Design and maintain dimensional data models, including facts and dimensions
• Partner with Finance, HR, and Operations leaders to translate business needs into data structures
• Build models supporting accurate, decision-ready reporting
• Implement testing, documentation, and data-quality checks
• Maintain clear data lineage and reporting transparency
• Ensure stakeholders trust reporting accuracy
• Own the data platform and make independent architectural and operational decisions

• Own end-to-end delivery of Data & AI programs across onshore and offshore teams
• Manage scope, budget, resource planning, delivery quality, and timelines
• Establish governance frameworks, delivery metrics, and operational excellence
• Ensure compliance with data governance, risk, security, and regulatory requirements
• Define enterprise data strategy, architecture, and modernization roadmaps
• Architect scalable Data Lakehouse, Data Warehouse, and AI platforms
• Drive automation, AI adoption, data quality, metadata management, lineage, and governance initiatives
• Champion innovation through Agentic AI, GenAI, and intelligent data operations
• Identify and develop opportunities in Data Modernization, AI, Analytics, Cloud Migration, and Data Governance
• Build trusted relationships with executive stakeholders and act as a strategic advisor
• Lead proposals, solution presentations, and SOW creation
• Drive business discovery workshops and transformation roadmaps
• Manage communications, risks, escalations, and stakeholder expectations
• Ensure alignment between business objectives and technology solutions

Lead Data Architect

• Develop and operationalize data pipelines for reports and advanced analytics
• Design, develop, maintain, and optimize Snowflake and AWS data pipelines, reporting solutions, and data products
• Build scalable ingestion, transformation, validation, and publishing processes
• Translate business requirements into technical designs, user stories, process flows, and scalable solutions
• Develop and maintain technical documentation, solution designs, operational runbooks, and supporting artifacts
• Integrate data across Member, Provider, Claims/Encounter, Quality, and Financial domains
• Implement data quality, monitoring, validation, reconciliation, automated testing, and exception-management frameworks
• Support cloud modernization and migration of legacy platforms to Snowflake and AWS
• Troubleshoot production issues, perform root-cause analysis, and implement sustainable solutions
• Establish engineering best practices across source control, CI/CD, automation, testing, documentation, and cloud architecture
• Collaborate within Agile delivery teams through planning, estimation, testing, deployment, and continuous improvement
• Partner with business and technology stakeholders to improve operational efficiency and deliver high-quality data solutions