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 Principal Engineer– Data Platform & Backend to lead the evolution of scalable data platforms, data pipelines, and data-intensive backend services powering digital experience, commerce, and customer intelligence platforms.

This is primarily a data platform engineering hands-on leadership role, with backend engineering as an important enabling capability. The ideal candidate will own modern data architecture, batch and streaming pipelines, data models, data qual ity, governance, and cloud- scale data systems, while also designing APIs, services, and integrations that make trusted data accessible, reliable, and product-ready.
 

This is a high-impact technical hands-on leadership role responsible for defining architecture, scaling data platforms, and enabling AI-driven personalization, experimentation, customer intelligence, 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 technical vision.

Roles & Responsibilities

• Lead the architecture and implementation of scalable enterprise data platforms, data pipelines, and data products.
• Design and build batch, real-time, and event-driven data processing systems.
• Own data architecture patterns including data modeling, lakehouse design, data
• contracts, schema evolution, lineage, quality, and governance.
• Build reliable data ingestion, transformation, orchestration, and serving layers for
• digital experience, commerce, customer intelligence, analytics, operational reporting, and AI/ML readiness.
• Design data-intensive backend services, APIs, and integrations that expose trusted
• data to products, platforms, and internal consumers.
• Define standards for ETL/ELT, streaming, data validation, observability, monitoring,
• metadata management, and pipeline reliability.
• Work with cloud and data platforms such as AWS, Azure, Snowflake, Databricks,
• Delta Lake, Apache Iceberg, Spark, Kafka/Kinesis, Airflow, dbt, and Fivetran.
• Partner with Engineering, Product, Data Science, Analytics, DevOps, Security, and
• FinOps teams to translate business and platform needs into scalable data solutions.
• Optimize data systems for performance, reliability, cost, security, and operational
• excellence.
• Contribute to technical roadmap planning, platform modernization, technical debt
• reduction, and adoption of modern data architecture patterns.
• Mentor engineers and raise the engineering bar across data design, implementation, testing, observability, operations, and ownership.

Minimum Qualifications

• 9+ years of hands-on engineering experience, with strong experience in data
• engineering, data platforms, or distributed data systems.
• 3+ years in a technical leadership role such as Principal Engineer, Staff Engineer,
• Architect, or Tech Lead.
• Proven experience designing and operating large-scale data platforms, pipelines, and data-intensive systems.
• Strong expertise in SQL, Python, data modeling, distributed systems, and cloud
• data architecture.
• Hands-on experience with modern data platforms such as Snowflake, Databricks,
• Delta Lake, Apache Iceberg, or equivalent.
• Experience with batch and streaming technologies such as Spark, Kafka, Kinesis,
• Flink, or equivalent.
• Experience with orchestration and transformation tools such as Airflow, dbt,
• Fivetran, Dagster, or equivalent.
• Good backend engineering experience with APIs, microservices, event-driven
• architecture, and service-to-data platform integrations.
• Experience with cloud platforms such as AWS and/or Azure.
• Strong understanding of data quality, governance, lineage, observability, schema
• evolution, CI/CD, and production operations.
• Ability to make pragmatic architecture decisions that balance scalability, reliability,
• delivery speed, and cost.
• Strong communication, stakeholder management, mentoring, and technical leadership skills.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical
• experience.