Senior Principal Data Engineer

Job Requisition ID #

26WD96752

Position Overview

Autodesk is a global leader in 3D design, engineering, and entertainment software, empowering innovators to design and make a better world. Our platforms support millions of users across industries including architecture, engineering, construction, manufacturing, and media. The Growth Experience Technology (GET) organization is seeking a Senior Principal Data Engineer to lead the evolution of our enterprise data ecosystem powering digital experience, commerce, and customer intelligence platforms.

This is a high-impact technical leadership role responsible for defining architecture, scaling data platforms, and enabling AI-driven personalization and decision intelligence at global scale. You will operate across multiple teams as a technical authority, mentor, and strategic driver, shaping both execution and long-term vision.

Responsibilities

Technical Leadership & Architecture

• Own and drive the end-to-end data architecture strategy for large-scale distributed data platforms supporting analytics, Applied AI, and personalization
• Design and oversee highly scalable, low-latency data pipelines (batch and streaming) for real-time and near real-time use cases
• Lead architectural decisions across technologies such as Snowflake, Spark, Flink, Iceberg, Kafka, and AWS ecosystem
• Define and enforce data modeling standards (conceptual, logical, physical) across enterprise domains
• Evaluate and adopt emerging technologies, including Generative AI and AI-assisted engineering tools, to enhance platform capabilities

• Establish best practices for DataOps, including CI/CD, observability, data quality, testing frameworks, and reliability engineering
• Drive improvements in data quality frameworks, governance, lineage, and monitoring
• Standardize engineering patterns, frameworks, and reusable components across teams
• Lead the design and implementation of enterprise-grade ETL/ELT pipelines using tools such as DBT, Python, and SQL
• Ensure systems meet performance, scalability, security, and cost optimization requirements

• Architect platforms enabling model training, inference, and personalization at scale
• Support development of customer data platforms, behavioral analytics, and segmentation systems
• Enable Generative AI use cases, including intelligent data discovery, self-service analytics, and automation of data workflows

• Act as a force multiplier across multiple scrum teams (7-9 engineers per team), mentoring senior engineers and technical leads
• Provide guidance during critical production incidents, root cause analysis, and system recovery
• Drive alignment across engineering, product, architecture, and business stakeholders globally
• Influence and define technical strategy, roadmaps, and cross-organizational standards
• Represent engineering in executive-level discussions and cross-functional initiatives

• Translate business requirements (GTM, sales, finance, customer analytics) into scalable technical solutions
• Partner with product, analytics, and business teams to deliver actionable insights and data products
• Lead discussions on trade-offs, prioritization, and architectural decisions in ambiguous environments

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 12+ years of experience in software and data engineering for enterprise-scale systems
• Deep expertise in:
  
  
  • Data architecture & distributed systems design
  • Big data technologies: Spark, Flink, Kafka, Iceberg, Parquet
  • Cloud platforms: AWS (S3, Lambda, ECS/EKS, etc)
  • Data warehousing: Snowflake (preferred)
• Advanced proficiency in SQL, Python, and modern ELT frameworks (e.g., DBT)
• Strong experience in data modeling, query optimization, and performance tuning
• Proven experience building event-driven architectures and streaming pipelines
• Experience leading multi-team, global engineering initiatives
• Strong communication skills with ability to influence senior stakeholders

• Experience with GTM systems (sales planning, customer segmentation, subscription/consumption models)
• Background in customer data platforms (CDP) and behavioral analytics
• Experience delivering AI/ML pipelines or production ML systems
• Exposure to Generative AI applications in data engineering workflows
• Familiarity with observability tools such as Splunk, Dynatrace, or similar
• Experience leading large-scale platform migrations or modernization initiatives

• Recognized technical authority with a track record of delivering large-scale distributed data platforms
• Operates effectively at both hands-on technical depth and strategic leadership levels
• Strong advocate for engineering excellence, automation, and developer productivity
• Demonstrated ability to navigate ambiguity and drive alignment across organizations
• Passionate about leveraging data and AI to drive business transformation and innovation