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Well-known employer and popular data role, but seniority and specialization reduce applicant density.
Medium — strong core data engineering skills transfer, but finance and Snowflake domain preferences increase specificity.
High — explicit 8+ years, Snowflake expertise, and leadership plus finance-domain experience required.
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Design, develop, and maintain scalable data pipelines, data models, and data products within Snowflake to support Finance reporting, analytics, and operations.
Serve as the primary data engineering partner translating Finance stakeholder requirements into sustainable, scalable data solutions, driving adoption of data engineering best practices.
Develop and maintain dimensional models, improve data quality and reliability, and align Finance data solutions with Autodesk's architectural standards, including support for emerging AI-enabled analytics.
Expert-level proficiency with Snowflake and cloud data warehousing concepts.
Bachelor’s degree in Computer Science, Computer Engineering, or equivalent work experience; Master’s desirable.
8+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering roles including ETL/ELT pipeline development.
Strong SQL skills and expertise in dimensional modeling, data quality controls, testing frameworks, monitoring, and operational best practices.
Experienced in partnering closely with Finance BI Developers and Finance stakeholders to deliver business-aligned data solutions at scale.
Hands-on experience with modern data engineering tools and frameworks and a solid understanding of analytical data structures and data governance.
Demonstrated curiosity and working knowledge of AI technologies, especially generative AI and Large Language Models integrated into enterprise data environments.