Principal Data Engineer, User Success (Agentic Experiences)
Core
Architect and implement scale batch and streaming pipelines for large-scale product telemetry to support AI-native experiences, LLMs, and agentic workflows.
Role type
Principal Data Engineer (AI/ML infrastructure)
Builds
AI-ready data products, feature stores, RAG-based systems, and evaluation pipelines for agentic insights.
Domain
Software / AI & Machine Learning / Data Engineering
Deliverable
production ML models
Required skills
Python, PySpark, advanced SQL, Kafka, Flink, Spark Streaming, dbt, vector databases, AWS (EMR, Glue, S3, IAM, Lambda, Step Functions), data governance, ETL/ELT orchestration
Preferred skills
product telemetry, clickstream data, Airflow, Fivetran, modernizing fragmented data infrastructure
Technologies
Spark, Kafka, Flink, dbt, Snowflake, Redshift, Athena, Iceberg, Hive, AWS EMR, Glue, S3, IAM, Lambda, Step Functions, vector databases
Responsibilities
Architect and implement scale batch and streaming pipelines for large-scale product telemetry; Partner with AI/ML teams to operationalize feature engineering and feature stores; Ensure data quality and observability meet the needs of AI-driven decision systems; Guide build vs. buy decisions for data tooling and platforms; Improve instrumentation strategy to ensure high-quality behavioral data; Drive alignment on data standards, governance, and best practices.
Seniority
Principal, hands-on IC with architectural vision and cross-functional leadership
