Build, optimize, and maintain scalable AWS-based data pipelines and data lakes (Snowflake/Databricks). Implement streaming ingestion (Kinesis/Kafka), CDC, automated data quality checks, and ML-ready feature stores. Collaborate with Product, ML, and Analytics teams, own pipeline QA, observability, and participate in on-call rotations to resolve production data issues.

Lead analytics engineering work to design, build, and maintain dbt-based transformation pipelines, governed metrics/semantic layers, and analytics-ready data marts on Snowflake or Databricks. Ensure data quality with automated tests and observability, support product analytics and ML feature datasets, partner with Product/Engineering, mentor junior team members, and participate in on-call rotations.