Senior Director, Data Engineering

About the Role

The Senior Director, Data Engineering sits within Autodesk’s Growth Experience Technology organization and is responsible for defining and executing the company’s end‑to‑end data engineering strategy across batch and real‑time platforms. Reporting to senior leadership, the role partners with Platform & Architecture teams to build secure, scalable, and resilient data foundations that enable AI‑driven use cases and cost‑efficient operations for Finance, Marketing, Sales, Customer Success, and Digital (.com) teams. Success is measured by active business adoption, faster decision‑making, and sustained value from data investments. The position involves up to 25 % travel and is preferred hybrid in San Francisco, with increased travel for candidates based elsewhere. • Drive measurable data adoption outcomes (active users, decision velocity, revenue impact) across Finance, Marketing, Sales, and Digital teams. • Lead batch and real-time data engineering on platforms such as Spark, Databricks, Snowflake, BigQuery, Kafka, and Flink. • Design and maintain a common data model and standardized metrics for cross‑functional reporting. • Define and execute data lake strategies using modern table formats (Apache Iceberg, Delta Lake, Hudi) for scalable, cost‑efficient storage. • Establish SLA/SLO tiers for data freshness, availability, and quality, embedding lineage, observability, privacy, and compliance. • Partner with Data Science and Product teams to deliver AI/ML‑enabled analytics, feature stores, and AI‑ready data solutions. • Optimize data investment cost versus business value, ensuring spend drives revenue, margin, or efficiency improvements. • Evangelize data strategy and best practices across the COO & CFO organization to secure adoption. • Lead a multi‑level global data engineering organization, providing career growth, succession planning, and mentorship. • Set and track OKRs focused on adoption, reliability, cost efficiency, and compliance. • Communicate executive‑level strategy and influence cross‑functional stakeholders to align on data initiatives.

Key Responsibilities

• ▸batch engineering
• ▸real‑time streaming
• ▸data lake
• ▸feature store
• ▸cost efficiency
• ▸adoption metrics

What You Bring

• Minimum qualifications: 15+ years data engineering leadership, 8+ years managing large teams, expertise in Kafka/Flink/Spark Streaming, lakehouse platforms (Databricks, Snowflake, BigQuery), Apache Iceberg, MDM principles, enterprise data modeling, governance, lineage, and cost optimization. • Preferred qualifications: experience delivering LLM/RAG/AI‑powered real‑time systems, designing domain‑oriented data contracts, building ecommerce personalization or finance reconciliation pipelines, and familiarity with CDC pipelines and eventing standards (CloudEvents, Avro, Protobuf).

Requirements

• ▸kafka
• ▸flink
• ▸spark
• ▸databricks
• ▸snowflake
• ▸llm

Benefits

Compensation includes a base salary range of $210,800‑$341,000 (U.S. roles), with potential bonuses, stock grants, and a comprehensive benefits package covering health, financial security, and wellness. Autodesk is an equal‑opportunity employer that values diversity and considers all qualified applicants without regard to protected characteristics or criminal histories. Additional information about benefits and the company’s commitment to diversity and belonging is available on its website.

Work Environment

Hybrid