Principal Data Engineer

Position Overview 

As a member of the Autodesk Finance Transformation team, you will be responsible for designing, developing, and maintaining data platforms, pipelines, and products that support operational reporting, AI agents and applications, dashboards, metrics, and financial decision-making for our partners across Finance. This position will play a key role in our continuing drive to advance the maturity of Finance-owned data products and engineering best practices within the Finance BI organization.

The ideal candidate will bring deep technical expertise in modern data engineering practices.  In this role, you will partner closely with Finance stakeholders, Finance BI Developers, Analytics teams, and the Growth Experience Technology (GET) organization to build reliable, scalable, and governed data solutions.

As Finance expands its use of AI-enabled analytics, this role will help develop data products that support not only traditional reporting and dashboarding, but also emerging LLM-powered exploration and future agentic workflows. Candidates should demonstrate curiosity about AI technologies and possess a working understanding of how Large Language Models interact with enterprise datasets and modern development tools.

Responsibilities

• Design, develop, and maintain scalable data pipelines, data models, and data products within Snowflake to support Finance reporting, analytics, and business operations
• Act as the primary data engineering partner for Finance BI Developers and business stakeholders, helping translate business requirements into sustainable and scalable data solutions
• Drive adoption of data engineering best practices, including data modeling standards, testing frameworks, monitoring, documentation, governance, and operational excellence
• Balance business requirements with technical feasibility and set expectations. Determine the size of requests and communicate effort, dependencies, and priorities to management
• Design and maintain dimensional models, curated data layers, and reusable datasets that support reporting, dashboarding, and self-service analytics
• Improve data quality, reliability, performance, and maintainability across Finance-owned data products and pipelines
• Partner with engineering teams to align Finance solutions with broader architectural standards at Autodesk
• Maintain up-to-date knowledge of modern data engineering tools, technologies, and industry best practices

Minimum Qualifications

• Expert-level proficiency with Snowflake and modern cloud data warehousing concepts
• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent work experience, Master’s degree desirable
• 8+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering roles
• 8+ years of experience developing and maintaining ETL/ELT pipelines and enterprise-scale data solutions
• Strong proficiency with SQL and experience with modern data engineering tools and frameworks for orchestration, transformation, and automation
• Strong understanding of dimensional modeling, data warehousing concepts, and analytical data structures
• Experience leading projects to implement data quality controls, testing frameworks, monitoring, and operational best practices
• Strong analytical and problem-solving skills
• High self-motivation and strong delivery focus
• Excellent teamwork and relationship development skills

Preferred Qualifications

• Experience supporting Finance, Sales Finance, Revenue Operations, or FP&A organizations within a subscription-based software or SaaS business
• Significant Technical Lead experience
• Working knowledge of BI and analytics platforms such as Power BI, Tableau, Qlik Sense, or similar technologies
• Demonstrated experience in generative AI technologies, with hands-on experience  building applications that leverage Large Language Models
• Familiarity with emerging AI application architectures, including agentic workflows, AI Skills, Model Context Protocol (MCP) servers, and related technologies
• Experience using AI-assisted development tools such as Claude Code, GitHub Copilot, Cursor, or similar platforms to improve engineering productivity and solution quality

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