Senior Data Architect – Enterprise Data Strategy

Job Requisition ID #

Position Overview

Autodesk is seeking a Senior Data Architect to join our Data Architecture team, which is responsible for defining and evolving the long-term data architecture vision.

This role operates at the strategic layer of architecture — shaping how data is structured, governed, activated, and leveraged across operational systems (Sales, Marketing, Support, Finance), customer-facing platforms (digital experience, subscriptions, personalization), and analytics and AI/ML ecosystems.

While this is a strategy-defining role, it is not purely conceptual. The ideal candidate is deeply technical and hands-on — capable of whiteboarding system flows, refining logical data models, reviewing integration designs, and mentoring engineers and architects to ensure the strategy is grounded in implementation reality. A critical dimension of this role is the ability to proactively identify opportunities to unlock enterprise data for AI-driven workflows — enabling automation, intelligent decisioning, personalization, and new product capabilities through well-architected, trusted data foundations. You will partner with senior enterprise and solution architects to ensure Autodesk’s data ecosystem evolves cohesively and scales to support new business models, customer experiences, and AI-powered innovation.

Key Responsibilities

• Establish and evolve the enterprise data architecture vision aligned to Autodesk’s business strategy and digital transformation goals

• Define enterprise data domains and ownership models across operational, customer, and analytical ecosystems

• Develop guiding principles and guardrails for how data is created, shared, mastered, governed, and activated

• Shape architectural patterns that support data products, domain-oriented ownership, and modern data paradigms

• Identify enterprise data assets that can be activated to power AI/ML, personalization, automation, and intelligent decisioning

• Design architectural patterns that make high-quality, governed data accessible for AI workflows across the organization

• Ensure machine learning pipelines and AI systems are grounded in authoritative enterprise data domains

• Partner with AI/ML and product teams to define scalable, reusable data foundations for experimentation and production AI systems

• Remove systemic barriers that limit data discoverability, accessibility, and reuse

• Create and maintain high-level conceptual and logical data models spanning CRM, ERP, Finance, subscription systems, marketing platforms, support systems, and analytics environments

• Design and validate end-to-end data flows that traverse multiple enterprise systems

• Identify architectural fragmentation and define modernization strategies

• Ensure operational and analytical architectures are cohesive and mutually reinforcing

• Engage directly in whiteboarding sessions, integration design reviews, and model refinement with engineering teams

• Guide translation of conceptual and logical models into implementable physical designs

• Review APIs, event schemas, data contracts, and pipeline architectures to ensure alignment with enterprise standards

• Provide practical implementation guidance for AI/ML, personalization, and real-time data use cases

• Lead by example with architectural artifacts that engineering teams can operationalize

• Partner with business, product, and engineering leaders to align data capabilities with business priorities

• Collaborate with enterprise and domain architects to align roadmaps and architectural decisions

• Influence funding and roadmap decisions before delivery begins

• Facilitate architectural governance processes and design reviews

• Establish scalable approaches for data management and authoritative data sources

• Define patterns for data contracts, lineage, observability, and quality validation

• Ensure architecture supports privacy, compliance, security, and financial controls

• Embed governance into architecture without creating unnecessary process overhead

• Mentor data architects and senior engineers on modeling, integration patterns, and system design

• Elevate architectural maturity across distributed global teams

• Drive consistency in architectural documentation and decision-making frameworks

• Foster a culture of pragmatic, business-aligned, AI-ready data thinking

Minimum Qualifications

• 10+ years of experience in software and data architecture roles in complex enterprise environments

• Demonstrated ex