Principal Data Engineer

Job Requisition ID #

26WD96683

Position Overview

We are hiring a Principal Data Engineer to join Autodesk's Enterprise Data Management (EDM) team within the COO-GET organization. In this senior technical leadership role you will lead the design and delivery of scalable data platform services, robust data products, and enterprise-wide data engineering standards that power canonical records and analytics across the company. You will partner across product, platform, and business stakeholders to translate complex business needs into pragmatic, high-quality technical solutions and to raise engineering maturity across multiple teams. Familiarity with master data management, data enrichment, identity resolution, and data quality practices is a plus.

• Act as a technical leader and force multiplier across multiple data engineering teams: coach, mentor, and raise the bar on code quality, testing, and delivery practices
• Define and own architecture and standards for data platform services, including data modeling, ETL/ELT patterns, metadata, and data governance
• Lead design and delivery of robust, performant data pipelines and data products using modern cloud data platforms (e.g., Snowflake), orchestration, and transformation tooling (dbt or similar)
• Drive DataOps maturity: testing frameworks, automated quality gates, CI/CD, observability, incident response, and runbooks for production data workloads
• Solve complex, enterprise-scale data engineering challenges (record reconciliation, identity/organizational hierarchies, lineage, scale/performance)
• Lead root-cause analysis and durable remediation for complex production incidents; enable teams to prevent recurrence
• Collaborate closely with product managers, data stewards, analytics, ML, and business stakeholders to prioritize high-impact initiatives and translate requirements into scalable engineering solutions
• Provide hands-on implementation as needed (POC, spike, or production work), and lead technical decision-making across teams
• Design and operationalize real-time/near-real-time data paths and evented architectures as appropriate to use cases.

• BS/MS in Computer Science or a related technical field, or equivalent practical experience
• 10+ years of hands-on software and data engineering experience in enterprise environments
• Deep, demonstrable expertise with SQL, hive, dbt, Python & Snowflake, and modern data engineering tooling (Snowflake and dbt or comparable technologies)
• Strong experience designing data models (conceptual, logical, physical) and optimizing query performance at scale
• Practical experience with data lake table formats and query engines (for example, Apache Hive, Apache Iceberg)
• Extensive AWS experience and comfortable designing solutions using cloud services and IaC (Terraform/CloudFormation)
• Track record of leading architecture and solution design for complex, cross-team systems
• Demonstrated ownership of data quality frameworks, observability, and production reliability for data workloads
• Excellent communication skills and experience influencing stakeholders across GEOs and functions
• Proven experience mentoring engineers and elevating team delivery practices.

• Prior experience in ingesting, aggregating, event streams, web & product analytics data
• Practical experience with streaming/event-driven architectures and stream processing frameworks (for example, Apache Flink)
• Familiarity with search/indexing systems and integrating with data APIs
• Experience operationalizing ML/AI or GenAI capabilities on enterprise data platforms