Senior Data Engineer - AI Infrastructure

Design and implement large-scale data pipelines using PySpark and distributed processing frameworks Build and maintain data models that accurately represent underlying system behavior and business logic Ensure high standards of data correctness, completeness, and consistency across datasets Develop validation, monitoring, and alerting mechanisms to detect data quality issues Partner with data scientists to support experimentation and analytics use cases Collaborate with platform engineers to ensure efficient data ingestion, processing, and storage Optimize pipelines for performance, scalability, and cost efficiency Define and enforce best practices for schema design, data transformations, and pipeline reliability Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. Experience with Azure technologies such as: Experience working with structured and semi-structured data (e.g., JSON logs) Experience with orchestration tools (e.g., Airflow) Experience building and operating large-scale data pipelines Experience ensuring data quality and correctness in production systems Experience working with cloud-based data platforms (Azure, AWS, or GCP) Ability to reason about data at scale, including performance and failure modes