AIML Data Engineer

What you'll do

• Design and maintain scalable data pipelines to ingest and transform support interaction data for LLM-based scoring systems.
• Engineer features and data transformations including metadata enrichment, schema normalization, and prompt context assembly for AI consumption.
• Build telemetry pipelines to track model performance, scoring accuracy, and concept drift across evaluation dimensions.
• Develop and operate pipeline orchestration workflows to ensure reliable and timely data delivery across AIML workstreams.
• Implement data quality checks, validation, and monitoring for pipeline health, data freshness, and scoring latency.
• Conduct root cause analysis to diagnose whether metric shifts are driven by data, models, or actual customer experience changes.
• Partner with program managers to perform targeted investigations, isolate variables, and quantify the impact of specific support experiences.
• Proactively surface anomalies and trends from pipeline telemetry to identify opportunities before they become escalations.

What we're looking for

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field (or equivalent experience).
• 4+ years of experience in data engineering or analytics engineering.
• Strong proficiency in SQL and Python for both data engineering and analytical investigation.
• Experience with cloud data platforms such as Snowflake or Databricks.
• Experience with ETL/ELT tools and pipeline orchestration like dbt, Airflow, or Prefect.
• Experience with version control (Git) and CI/CD practices.
• Demonstrated ability to conduct root cause analysis and translate data findings into actionable recommendations.
• Experience building data pipelines supporting LLM-based systems (preferred).