Description

About the Role 

Internet Brands is seeking an Associate AI Data Engineer to join the Personalization & Data Management function within our Central AI Team. This position supports WebMD, enabling data-driven personalization and AI-powered experiences that help millions of consumers connect with trusted health information, providers, and products. 

Role Overview:

In this role, you’ll build and optimize the data infrastructure that powers personalization, recommendations, and predictive insights across our consumer health platforms. You’ll collaborate closely with AI engineers, data scientists, and product managers to ensure our data pipelines deliver clean, actionable, and privacy-compliant data that fuels intelligent engagement across multiple health brands. 

Key Responsibilities 

• Design, build, and maintain scalable data pipelines that collect and transform data from health content, consumer behavior, provider interactions, and marketing systems. 
  
• Enable personalization and recommendation engines by ensuring high-quality, real-time, and batch data delivery across consumer touchpoints (web, mobile, and email).
  
• Integrate data from multiple sources including content management systems, analytics platforms, CRM, and marketing tools into unified data stores that support AI model training and personalization workflows.
  
• Partner with Data Scientists and ML Engineers to operationalize AI models, ensuring seamless data access, feature pipelines, and model monitoring.
  
• Implement data validation, quality, and observability frameworks to ensure reliability and compliance with healthcare privacy standards (HIPAA, GDPR, CCPA).
  
• Collaborate with the AI Engineering and Health Product teams to improve data architecture and pipeline efficiency for consumer health use cases.
  
• Maintain and enhance data cataloging, documentation, and lineage tracking, contributing to a well-governed central data ecosystem.
  
• Continuously evaluate and apply emerging AI data engineering practices to improve scalability, automation, and intelligence in personalization systems. 
  

Qualifications Required:

• Bachelor’s degree in Computer Science, Data Engineering, or a related technical field. 
  
• Proficiency in Python, SQL, and modern ETL/ELT frameworks (Airflow, dbt, Dagster, etc.)
  
• Experience with cloud data infrastructure (AWS Glue, S3, Redshift, BigQuery, or Snowflake).
  
• Strong understanding of data modeling, transformation, and schema design for analytics and AI.
  
• Experience working with structured and semi-structured data (JSON, Parquet, CSV) and integrating with third-party APIs.
  
• Familiarity with machine learning data flows and model-serving requirements.
  

Preferred: 

• Experience in the health, wellness, or consumer engagement domain. 
  
• Familiarity with PII and PHI data handling, data anonymization, and compliance frameworks.
  
• Exposure to personalization or recommendation systems, audience segmentation, or behavioral targeting.
  
• Knowledge of data lakehouse environments (Databricks, Snowflake, or similar) and feature store architectures.
  
• Experience with data quality and observability tools (e.g., Great Expectations, Monte Carlo, DataHub).