Principal Data Engineer, Growth Analytics

Autodesk

Principal Data Engineer at Autodesk leading design and development of analytics infrastructure. Building scalable data environments using Snowflake for internal stakeholders and product/ops teams.

Posted 6/3/2026full-timeRemote • Massachusetts • 🇺🇸 United StatesLead💰 $128,000 - $229,900 per yearWebsite

Tech Stack

Tools & technologies

AirflowPySparkPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

8+ years of experience in data engineering, analytics engineering, or 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 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
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

Benefits

Comp & perks

health and financial benefits
time away and everyday wellness

ATS Keywords

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Hard Skills & Tools

data engineeringanalytics engineeringdata platformsdata infrastructureSnowflakeScriptingSQLPythondata modelingdata quality

Soft Skills

communicationmentoringcollaborationtechnical designdocumentation