Principal Data Engineer, Growth Analytics

Autodesk is a company that creates innovative software for a variety of industries. They are seeking a Principal Data Engineer to lead the design and development of their analytics foundational data environment, focusing on building internal data infrastructure and supporting strategic decision-making through data. This role involves hands-on technical leadership and collaboration with internal stakeholders to shape how data is utilized within the organization.

Responsibilities:

• Architect and build the core Growth Analytics data environment with Snowflake as the central platform
• Design, implement, and maintain scalable data pipelines, integrations, and transformation workflows across internal business, product, operational, sales, marketing, finance, and planning systems
• Build trusted, reusable data models and curated datasets to support internal analytics, reporting, forecasting, growth planning, and Strategy & Operations workflows
• Develop and manage BI environments in Power BI and Looker, including semantic models, governed datasets, dashboard foundations, access patterns, and performance standards
• Build AI-ready data layers to support internal intelligence solutions, including structured datasets, metadata, documentation, business definitions, and governed access patterns
• Establish standards for data quality, testing, observability, lineage, documentation, naming conventions, metric definitions, and production reliability
• Partner with internal stakeholders to translate business questions into scalable data products, reporting layers, and analytics-ready infrastructure
• Create and maintain clear documentation for source systems, pipelines, data models, metric definitions, BI assets, and AI-ready datasets
• Lead technical design discussions, make architecture recommendations, and mentor analytics, BI, and data partners on scalable data practices
• Help move AOS from fragmented reporting and manual data processes toward a reliable, governed, and scalable intelligence layer

Requirements:

• 8+ years of experience in data engineering, analytics engineering, data platform engineering, or a related technical role
• Proven experience building data platforms, analytics environments, or major data infrastructure from scratch or through significant transformation
• Deep hands-on experience with Snowflake
• Strong Scripting, SQL and Python skills
• Experience building production-grade pipelines, integrations, orchestration workflows, and transformation logic
• Experience with modern data ingestion tools ingestion tool such as Fivetran, Airflow + Python, dbt, Pyspark or similar technologies
• Experience building BI environments such as Power BI or Looker
• Strong understanding of data modeling, semantic layers, governed metrics, access control, documentation, lineage, data quality, and observability
• Experience preparing data infrastructure for AI, ML, LLM, advanced analytics, or internal intelligence use cases
• Ability to work with ambiguity, clarify requirements, and turn business needs into scalable technical solutions
• Strong communication skills with technical and non-technical stakeholders
• Experience supporting internal analytics, growth analytics, product Strategy & Operations, GTM analytics, finance analytics, or business operations teams
• Experience integrating data from systems such as Salesforce, Marketo, finance platforms, product usage systems, planning tools, and operational systems
• Experience creating AI-ready data assets, metadata layers, governed knowledge layers, feature-ready datasets, or semantic models
• Experience designing standards for BI development, data documentation, metric governance, and data product delivery
• Experience in B2B SaaS, enterprise software, or complex matrixed organizations
• Track record of building zero-to-one data infrastructure in an environment with fragmented systems, evolving requirements, and limited existing standards