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# Principal Data Engineer

- **Company:** BINGHAMTOM UNIVERSITY
- **Location:** United States
- **Experience:** Expert
- **Salary:** $128,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Apache HTTP Server, Information Engineering, Data Governance, GEOS, Apache Hive, Cloud Services, Systems Integration, Enterprise Data Management, Snowflake, Generative AI, Cloudformation, Event Driven Architecture, Data Lakes, Apache Flink, Terraform, Stream Processing, Autodesk Autocad
- **Published:** July 14, 2026
- **Apply:** https://www.themuse.com/jobs/autodesk/principal-data-engineer-e14df0?utm_source=uconnect

## About the Role

* 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

## Description

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.


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