Position Overview

At Autodesk, we do what no other company can: we help our customers design and make anything. The Experience Foundations team at Autodesk plays a critical role in designing the experiences that make that mission a reality, especially in this transformative moment where seamless digital experiences and AI-powered innovation will empower customers and teams to achieve meaningful outcomes faster.

The Principal Data Engineer will report to Director of Growth and Data Science in the Experience Foundations organization. This is a critical data science role for our agentic insights platform—we are evolving our data tools and platform to support AI-native experiences, enabling both humans and intelligent systems to better understand user behavior and business impact.

As a Principal Data Engineer, you will be driving the design of AI-ready data products that power analytics, machine learning, and emerging agentic experiences and insights and intelligence products.

This role requires a balance of deep technical expertise, architectural vision, and cross-functional leadership, influencing how data is structured, governed, and consumed across Autodesk.

Responsibilities

• Architect and implement scale batch and streaming pipelines for large-scale product telemetry with low-latency, high-throughput data access that support LLMs and agentic workflows optimized for:

  • Real-time and iterative feedback loops

  • Contextual data access

  • Retrieval (e.g., embeddings, vector search)

• Partner with AI/ML teams to operationalize:

  • Feature engineering and feature stores

  • RAG-based systems and evaluation pipelines

• Ensure data quality and observability meet the needs of AI-driven decision systems

• Guide build vs. buy decisions for data tooling and platforms

• Enable analysts and product teams with trusted, well-modeled datasets

• Partner with stakeholders to translate product questions into measurable data signals

• Improve instrumentation strategy to ensure high-quality behavioral data

• Support self-service analytics and AI-assisted exploration

• Collaborate across Product, Engineering, Data Science, Research and Design

• Influence technical direction without direct authority

• Drive alignment on data standards, governance, and best practices

• Communicate complex technical concepts to both technical and non-technical audiences

Minimum Qualifications

• 10+ years of experience in data engineering, data platform engineering, distributed systems, or related technical roles, including ownership of large-scale production data systems

• Strong hands-on experience with Python, Spark, PySpark, advanced SQL, and scripting

• Experience with:

  • LLM ecosystems, embeddings, vector databases

  • Retrieval-augmented generation (RAG)

  • Agent frameworks or orchestration systems

• Experience with streaming technologies (Kafka, Flink, Spark Streaming)

• Knowledge of analytics engineering and semantic layer tools (dbt, metrics stores)

• Experience with data governance, lineage, and cataloging systems

• Exposure to product analytics and experimentation frameworks

• Experience designing and operating reliable ETL/ELT pipelines across batch and streaming workloads, including orchestration, validation, backfills, incremental processing, and data quality checks

• Experience with modern data platforms, including Iceberg, Hive, Snowflake, Redshift, Athena, or equivalent technologies

• Hands-on experience with AWS services, including EMR, Glue, S3, IAM, Lambda, Step Functions, and related cloud-native infrastructure

• Demonstrated ability to lead cross-functional technical initiatives, influence architecture, define engineering standards, and mentor engineers

• Strong communication skills with technical and non-technical stakeholders

Preferred Qualifications

• Experience with product telemetry, clickstream data, behavioral analytics, or experimentation platforms

• Experience with ingestion, orchestration, and transformation tools such as Airflow, dbt, Fivetran, or similar

• Experience partnering with product, design, research, analytics, and ML teams to create data products that directly inform user experiences or power intelligent product capabilities

• Experience supporting LLM, RAG, agentic AI, or internal intelligence workflows in production or enterprise environments

• Track record of modernizing data infrastructure in environments with fragmented systems, evolving requirements, or limited standards

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

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