Principal Data Engineer, Analytics
Job in
Boston, Suffolk County, Massachusetts, 02133, USA
Listed on 2026-06-05
Listing for:
Autodesk
Full Time
position Listed on 2026-06-05
Job specializations:
-
IT/Tech
Data Analyst, Data Engineer, Data Science Manager, Business Systems/ Tech Analyst
Job Description & How to Apply Below
** Job
Requisition #*
* 26WD98669
** Position Overview*
* Autodesk Operation Solutions is hiring a
** Principal Data Engineer
** to build the Analytics foundational data environment. This role will lead the design and development of internal data infrastructure, system connections, pipelines, BI environments, AI-ready data layers, documentation, etc. that serve AOS internal stakeholders and product/ops teams. The role has high visibility, broad internal impact, and the chance to shape how AOS uses data, BI, and AI to support planning, operations, growth, and strategic decision-making.
This is a hands-on technical leadership role for someone who has built analytics infrastructure from the ground up. The ideal candidate is strong in Snowflake, fluent in modern data engineering practices, and comfortable creating the data foundation required for business intelligence, advanced analytics, and AI-enabled decision support.
** 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
** Minimum Qualifications*
* + 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…
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