Principal Data Engineer

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Job Requisition

Location:

Portland, OR

We are seeking a Principal Data Engineer to provide technical leadership in designing, building, and scaling data infrastructure that powers machine learning, personalization, and search experiences. You will architect scalable data pipelines in production, drive technical strategy, and mentor engineering teams while partnering with Machine Learning Engineering, Platform Engineering, and Data Science.

Your work will be critical to strategic initiatives including optimization of digital conversion metrics, development of Autodesk Assistant (an LLM‑driven chatbot), RAG (Retrieval‑Augmented Generation) systems, eCommerce personalization engines, and intelligent search capabilities. As a Principal Engineer, you will set technical direction, establish best practices, and drive innovation across the data engineering organization.

Our team culture is built on collaboration, mutual support, and continuous learning. We emphasize an agile, hands‑on, and technical approach at all levels of the team.

• Define and drive technical architecture for data platforms supporting ML and personalization at scale.
• Design, build, and maintain highly scalable, low‑latency data pipelines supporting real‑time ML inference and personalization.
• Build data pipelines for RAG systems, including vector embeddings and semantic search.
• Design real‑time feature engineering and event processing systems for eCommerce personalization and recommendation engines.
• Develop sophisticated data models optimized for ML training, real‑time inference, and analytics workloads.
• Implement complex stream processing architectures using technologies like Kafka and Flink.
• Oversee and optimize database systems (SQL, No
  
  SQL, vector databases) ensuring high performance and scalability.
• Establish data engineering standards, patterns, and best practices across the organization.
• Provide technical leadership, guidance, and mentorship to senior and mid‑level data engineers.
• Lead cross‑functional teams to deliver complex data engineering solutions in production.

• 8+ years of data engineering experience with at least 3+ years in a senior or lead capacity.
• Expert‑level proficiency in Python, Java, or Scala.
• Deep knowledge of SQL and extensive experience with relational and No
  
  SQL databases.
• Strong expertise in big data technologies (Kafka, Flink, Spark, Parquet, Iceberg, Delta Lake).
• Advanced experience with ETL orchestration tools like Apache Airflow.
• Extensive experience with cloud platforms (AWS, Azure, or GCP) and their data services.
• Deep understanding of data warehousing solutions like Snowflake, Redshift, or Big Query.
• Proven expertise in data modeling, data architecture design, and ETL/ELT processes at scale.
• Demonstrated ability to lead technical initiatives and mentor engineering talent.
• Strong communication skills with ability to explain complex technical concepts to diverse audiences.
• Bachelor’s degree in computer science or related field (Master’s/PhD strongly preferred).

• Experience building data pipelines for Retrieval‑Augmented Generation, vector databases (Pinecone, Weaviate, Milvus), and semantic search.
• Experience with real‑time personalization engines, recommendation systems, feature stores, and A/B testing infrastructure.
• Experience building ML data pipelines, feature engineering systems, and model serving infrastructure.
• Knowledge of search technologies (Elasticsearch, Solr, Open Search), relevance tuning, and search analytics.
• Deep experience with event streaming, behavioral analytics, and customer data platforms.
• Experience with A/B testing infrastructure and metrics computation at scale.
• Knowledge of MLOps, model monitoring, and ML pipeline orchestration.
• Knowledge of eCommerce metrics, conversion optimization, and digital analytics.

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