Principal Data Engineer, User Success
Core
Architecting and implementing large-scale batch and streaming data pipelines to power AI-native experiences, agentic workflows, and analytics for Autodesk's product telemetry.
Role type
Principal Data Engineer (AI/ML infrastructure)
Builds
AI-ready data products, feature stores, RAG-based systems, and scalable data platforms for agentic insights.
Domain
Software / AI & Machine Learning / Data Engineering
Deliverable
production ML models | infrastructure
Required skills
Python, PySpark, advanced SQL, Kafka, Flink, Spark Streaming, vector databases, embeddings, RAG, AWS (EMR, Glue, S3, Lambda), dbt, data governance, ETL/ELT pipeline design
Preferred skills
product telemetry, clickstream data, Airflow, Fivetran, modernizing fragmented data infrastructure
Technologies
Spark, Kafka, Flink, Snowflake, Redshift, Athena, Iceberg, Hive, AWS EMR, Glue, S3, Lambda, Step Functions, dbt, Airflow, Fivetran
Responsibilities
Architect scale batch and streaming pipelines for product telemetry; Partner with AI/ML teams to operationalize feature engineering and RAG systems; Ensure data quality and observability for AI-driven decision systems; Guide build vs. buy decisions for data tooling; Enable analysts with trusted datasets; Improve instrumentation strategy for behavioral data; Drive alignment on data standards and governance.
Seniority
Principal, hands-on IC with cross-functional leadership
