Senior Director AI/ML Engineering - Remote

Primary Responsibilities

• Define and execute the enterprise data and AI engineering strategy aligned with business objectives and growth priorities
• Develop a multi-year roadmap for modernizing data platforms, analytics capabilities, and AI enablement
• Establish enterprise standards for data management, governance, quality, lineage, metadata, and observability
• Lead the design, implementation, and operation of modern cloud-based data platforms
• Leverage Databricks, Snowflake, and cloud-native services to establish enterprise architecture patterns
• Transform traditional reporting environments into AI-powered analytics ecosystems
• Promote adoption of AI for Business Intelligence, including natural language analytics, intelligent reporting, automated insights, and predictive decision support
• Enable self-service analytics capabilities that allow business users to access trusted data and insights
• Partner with analytics and business teams to deliver enterprise KPI frameworks and measurement standards
• Define and implement enterprise semantic layer architecture that delivers consistent business definitions and metrics across all reporting and analytics platforms
• Develop reusable business data models that simplify access to complex enterprise data
• Establish enterprise capabilities that enable scalable AI and machine learning development
• Build AI-ready data architectures supporting machine learning, generative AI, agentic AI, and advanced analytics

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or a related field
• 8+ years of progressive experience in data engineering, data architecture, analytics, or cloud data platforms
• 5+ years of experience building large-scale enterprise data platforms supporting analytics and AI workloads
• 5+ years of experience leading enterprise data modernization initiatives
• Deep expertise with Databricks, Snowflake, Lakehouse Architectures, Data Warehousing, Data Modeling, Semantic Layers, Cloud Data Platforms (Azure preferred), Modern ETL/ELT Frameworks, data Governance and Metadata Management
• Demonstrated success partnering with executive stakeholders and business leaders to translate data into business outcomes

Preferred Qualifications

• Master's degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline
• Solid understanding of business intelligence platforms, analytics engineering, and self-service analytics
• Solid communication and influencing skills with the ability to engage both technical and non-technical audiences
• Experience within PBM, healthcare, pharmacy, payer, financial services, or other highly regulated industries
• Deep understanding of healthcare and PBM data domains including claims, formulary, clinical, rebate, pricing, eligibility, and provider analytics
• Experience implementing enterprise semantic layers using modern analytics platforms
• Experience building data products and domain-oriented architectures
• Knowledge of Fabric, Power BI, dbt, Unity Catalog, Delta Lake, and modern metadata management platforms
• Experience enabling AI-powered BI and conversational analytics experiences
• Experience supporting Generative AI, RAG, and Agentic AI architectures through enterprise data services
• Solid understanding of data privacy, regulatory compliance, governance, and responsible AI frameworks
• Proven ability to lead complex enterprise transformations involving data, analytics, and AI capabilities