We are looking for an experienced Engineering Manager to lead our Batch Processing platform team — responsible for building and scaling a high-throughput, governed data platform that powers critical business decisions across the organization, including Autodesk's AI products such as Autodesk Assistant. This role sits at the intersection of high-scale platform engineering, data architecture, and organizational leadership. You will lead a team of strong engineers designing and operating large-scale distributed data processing systems on a modern lakehouse architecture, enabling reliable, secure, and cost-efficient data movement at petabyte scale.
We are looking for an experienced Engineering Manager to lead our Batch Processing platform team — responsible for building and scaling a high-throughput, governed data platform that powers critical business decisions across the organization, including Autodesk's AI products such as Autodesk Assistant. This role sits at the intersection of high-scale platform engineering, data architecture, and organizational leadership. You will lead a team of strong engineers designing and operating large-scale distributed data processing systems on a modern lakehouse architecture, enabling reliable, secure, and cost-efficient data movement at petabyte scale.
Responsibilities
Team leadership & delivery
Lead, mentor, and grow a team of strong engineers working on batch processing and data platform capabilities
Be an AI-native leader — leverage AI tools to drive rapid iteration, experimentation, and continuous product evolution
Drive roadmap execution with a focus on reliability, scalability, ease of use, and time-to-data
Establish a high-ownership culture with strong engineering fundamentals: design reviews, RCA, testing, and observability
Partner with TPMs and stakeholders to ensure predictable, high-quality delivery
Platform architecture & engineering
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Design and evolve a scalable, AI-friendly batch processing platform using Apache Spark (PySpark), distributed compute frameworks, workflow orchestration (Airflow / Temporal), Kubernetes controllers, and AI agents
Build systems capable of processing billions of records at petabyte scale
Enable self-service and AI-native pipeline capabilities for internal teams through clean, extensible APIs and platform abstractions
Optimize continuously for performance, cost efficiency, and reliability
Lakehouse & data ecosystem
Drive adoption of a modern lakehouse architecture (S3 + Apache Iceberg or equivalent)
Build self-service batch processing capabilities that enable internal teams to run Spark, Python, Ray, and MLOps jobs with minimal friction and strong platform guardrails
Enable downstream consumption via SQL engines and warehouse integrations
Governance, security & compliance
Ensure platform adherence to data governance and security standards
Build self-service controls and abstractions that allow teams to manage access, enforce data policies, and meet compliance requirements without deep platform expertise
Partner with security and compliance teams to meet enterprise and regulatory requirements
Observability & reliability
Build end-to-end observability: metrics, logging, alerting, SLA tracking, and reporting
Drive incident management, root cause analysis, and continuous improvement
Improve platform resilience through automation and resilience patterns
Stakeholder & cross-team collaboration
Partner with data engineering, analytics, and platform teams to drive adoption
Work closely with infra, security, and partner teams for platform integration
Influence architecture decisions at the org level
Communicate effectively with senior leadership and business stakeholders
Minimum qualifications
8–12+ years in software or data engineering
3–5+ years managing engineering teams
Experience leading platform teams or large-scale data systems
Strong hands-on experience with distributed data processing (Spark, Flink, etc.), batch pipelines at scale, and AWS (preferred)
Deep understanding of data lake / lakehouse architectures, data modeling, and workflow orchestration (Airflow, Temporal, etc.)
Proven ability to hire, mentor, and grow high-performing teams
Strong communication and cross-functional influence skills; ability to balance technical depth with strategic thinking
Preferred qualifications
Experience with Apache Iceberg or Delta Lake
Familiarity with data observability tools
Experience with metadata and catalog systems (e.g., Atlan or similar)
Exposure to data governance frameworks and compliance standards
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About Autodesk
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary transparency
Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
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About Autodesk
Software & SaaS14300 employeesFounded 1982
Global provider of software for design, engineering, and manufacturing.
