oracle
Lead Engineer, Big Data - Databricks - Remote
Molina Healthcare
USA
Onsite
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Provides lead level engineering support for information technology (IT) big data architecture activities on Microsoft Azure cloud infrastructure.
Representing as a Forward Deployed Engineer, responsible for leading the collection, storage, processing, and analysis of large health care payor datasets supporting Medicare/Medicaid operations.
Designs enterprise-scale data solutions on Azure Databricks, Azure Data Factory, and Azure Synapse with emphasis on performance, scalability, and high-reliability.
Champions AI-first practices, mentors team members, and drives adoption of machine learning and advanced analytics to improve member health outcomes.
Partners strategically with business leaders to identify data-driven opportunities and delivers end-to-end solutions.
Essential Job Duties
- Operates as a lead Forward Deployed Engineer, driving end-to-end ownership culture and mentoring team members on business problem-solving.
- Provides subject matter expertise in Azure data platform architecture (Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake).
- Champions AI-first development practices, implementing GitHub Copilot workflows and Azure Machine Learning solutions for predictive health care analytics.
- Designs and implements business intelligence (BI) solutions using Power BI, Tableau integrated with Azure data platform.
- Analyzes current business practices and identifies opportunities for leveraging Azure data and AI PaaS services to improve Medicare/Medicaid operations.
- Builds reusable data quality frameworks and automated data validation using Azure DevOps and quality assurance automation tools.
- Leads integration initiatives connecting Azure data platform with low-code platforms (Pega, Salesforce, Sitecore).
- Converts business requirements into technical architecture, design and implementation for health care analytics use cases.
- Designs analytical data models supporting self-service BI for clinical, financial, and operational stakeholders.
- Implements batch and real-time data pipelines for claims processing, quality metrics, and population health analytics.
- Partners with business leaders across the organization to identify high-value data opportunities and prioritize initiatives.
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