Principal Data Engineer
AutodeskAbout the role
Job Requisition ID #
26WD96683Position 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.
Responsibilities
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.
Minimum Qualifications
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.
Preferred Qualifications
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
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 ev
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