Vice President of Data Platforms, CodaMetrix

• 10+ years of experience in data engineering, data architecture, or data platform leadership roles with 5+ years leading data platform teams
• Expertise managing and scaling cloud-based data platforms particularly Databricks on AWS or Azure
• Deep experience designing and operating large scale data lakes, real-time and batch data pipelines, and streaming architectures
• Strong understanding of ML and AI data sourcing needs (labeled datasets, feature stores, etc.)
• Experience working with structured, semi-structured, and unstructured healthcare data (EHR, claims, clinical notes, HL7, FHIR) is highly desirable
• Strong knowledge of modern data technologies (Spark, Delta Lake, Kafka, Airflow, dbt, etc.)
• Solid grasp of data security, privacy, and compliance frameworks (HIPAA, SOC2, HITRUST)
• Excellent leadership, collaboration, and communication skills, with the ability to influence across technical and business teams
• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems or related field; advanced degree preferred

Desirable

• The Vice President, Data Platforms is a member of the Data & Analytics team, reporting to the Senior Vice President, Data & Analytics
• The Data & Analytics team consists of the Data Engineering, Business Intelligence, Customer Integrations and Data Analysis teams and is responsible for supporting all internal teams who consume data on a regular basis (Engineering, Machine Learning, Analytics, etc
• And developing data products for CMX customers
• The goal of the team is to develop and execute on the Data & Analytics strategy
• The Vice President, Data Platforms is responsible for maintaining the health of the Databricks Lakehouse platform and ensuring that all required data is sourced proactively and cost-effectively for CMX Machine Learning teams
• They are also accountable for all data ingestion, architecture, engineering and sourcing functions
• Own and evolve the Databricks Data Lake platform strategy, architecture, security, and operations
• Lead all data ingestion ETL/ELT, and data integration activities from internal and external sources
• Architect and oversee scalable data pipelines and services to source and curate high-quality datasets for machine learning, analytics, and business intelligence use cases
• Collaborate closely with machine learning, product, data analysis, integrations and engineering teams to prioritize data needs and ensure data availability, quality, and accessibility
• Build, lead, mentor a high-performing data engineering and data architecture team while establishing a robust sourcing function for machine learning
• Establish data governance, metadata management and data quality frameworks
• Optimize cost, performance, and operational efficiency of the data infrastructure
• Ensure compliance with HIPAA, SOC2, and other healthcare data security standards
• Develop and manage budgets, vendor relationships, and technology evaluations related to the data platform ecosystem
• Partner with senior leadership, including the Architecture committee, to align data platform initiatives with company goals and the product roadmap
• Work closely with engineering managers, machine learning, and implementations teams to understand the current state of data acquisition, processing, storage and usage
• Define, document, and communicate the data management lifecycle to all internal data stakeholders and participate as a key member of the Architecture Review Council
• Contribute as a member of the senior leadership team by driving the data initiatives for the company