Principal Data Engineer, Growth Analytics

About the role

The Principal Data Engineer will 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, develop and manage BI environments in Power BI and Looker, establish standards for data quality, testing, observability, lineage, documentation, naming conventions, metric definitions, and production reliability, and partner with internal stakeholders to translate business questions into scalable data products, reporting layers, and analytics-ready infrastructure.

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
• Strong 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 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
• 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
• Track record of building zero-to-one data infrastructure in an environment with fragmented systems, evolving requirements, and limited existing standards

Qualifications

• Strong 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 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
• 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
• Track record of building zero-to-one data infrastructure in an environment with fragmented systems, evolving requirements, and limited existing standards

Skills

• Strong 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 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
• 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
• Track record of building zero-to-one data infrastructure in an environment with fragmented systems, evolving requirements, and limited existing standards

Benefits

Autodesk offers a comprehensive benefits package including health and financial benefits, time away, and everyday wellness. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/.

Pay

For U.S.-based roles, we expect a starting base salary between $128,000 and $229,900. Offers are based on the candidate's experience and geographic location, and may exceed this range.

Schedule

N/A

Application Instructions

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