Principal Data Engineer

Responsibilities

• Architect and implement large-scale batch and streaming pipelines for product telemetry to support LLMs and agentic workflows
• Optimize data access for retrieval, including embeddings, vector search, and contextual data access
• Partner with AI/ML teams to operationalize feature engineering, feature stores, and RAG-based systems
• Ensure high data quality and observability for AI-driven decision systems
• Guide build vs. buy decisions for data tooling and platforms
• Collaborate across Product, Engineering, Data Science, and Design to translate product questions into measurable data signals
• Drive alignment on data standards, governance, and engineering best practices

Requirements

• 10+ years of experience in data engineering, data platform engineering, or distributed systems
• Strong hands-on expertise with Python, Spark, PySpark, and advanced SQL
• Proven experience with LLM ecosystems, embeddings, vector databases, and RAG frameworks
• Experience with streaming technologies such as Kafka, Flink, or Spark Streaming
• Proficiency with modern data platforms including Snowflake, Redshift, Iceberg, or Athena
• Hands-on experience with AWS services (EMR, Glue, S3, Lambda, Step Functions)
• Demonstrated ability to lead cross-functional technical initiatives and mentor engineers

Preferred Qualifications

• Experience with product telemetry, clickstream data, and behavioral analytics
• Experience with orchestration and transformation tools like Airflow, dbt, or Fivetran
• Track record of supporting LLM, RAG, or agentic AI workflows in production environments
• Experience modernizing data infrastructure in complex or fragmented environments

About the Company

Autodesk helps customers design and make anything, from the greenest buildings to the smartest factories. We empower innovators to turn their ideas into reality, transforming how things are made and what can be made.