Senior Data Software Engineer, Personalization

Autodesk Autodesk · Enterprise · Toronto, ON +1

Senior Data Software Engineer focused on building the data foundations for Autodesk's AI-powered personalization platform. This role involves designing and owning scalable data pipelines, backend services, and APIs to support personalization, ML, and agentic workflows. The engineer will work with complex data, ensure data quality and observability, and partner with data scientists and product managers.

What you'd actually do

  1. Design and build scalable data pipelines to ingest, process, and serve product usage and behavioral data for personalization and AI use cases
  2. Develop backend services and data APIs using technologies such as Python, Java, or Kotlin, and frameworks like Spring Boot, FastAPI, or similar
  3. Build and operate microservices that expose data and intelligence capabilities to internal and customer-facing applications
  4. Define and evolve data models, schemas, and transformations to ensure high-quality and reliable datasets
  5. Build systems that support AI and agentic workflows, ensuring data is structured and accessible for automated decision-making and intelligent agents

Skills

Required

  • BS or MS in Computer Science, Engineering, or a related field
  • 8 or more years of experience building production-grade software systems
  • Strong experience designing and building backend services and distributed systems using languages such as Python, Java, or Go
  • Experience with API design and development, including REST or gRPC-based services
  • Strong experience designing and operating large-scale data systems and distributed architectures in cloud environments, AWS preferred
  • Deep expertise in SQL and relational data modeling, including schema design, normalization, and performance optimization at scale
  • Strong understanding of data modeling concepts for analytical and operational systems, including building durable, reusable datasets
  • Experience building and operating data pipelines using tools like Airflow, Prefect, or similar
  • Experience working with cloud data platforms such as Snowflake, Hive, or Redshift
  • Strong understanding of data quality, testing, lineage, and monitoring in production systems
  • Ability to design and build scalable systems that serve high-volume data workloads

Nice to have

  • Experience with personalization, recommendation systems, or ML platforms
  • Experience with real-time or event-driven architectures such as Kafka or Kinesis
  • Familiarity with LLM-based systems, including building or supporting data pipelines for AI-driven applications
  • Experience working with or enabling agentic workflows or AI-powered automation
  • Experience collaborating closely with data science or ML teams
  • Experience mentoring engineers or leading technical initiatives

What the JD emphasized

  • 8 or more years of experience building production-grade software systems
  • Deep expertise in SQL and relational data modeling, including schema design, normalization, and performance optimization at scale
  • Strong understanding of data modeling concepts for analytical and operational systems, including building durable, reusable datasets

Other signals

  • building cloud-native, AI-powered platforms
  • democratize ML/Analytics
  • design and own the data foundations that power Autodesk’s personalization Platform capabilities
  • modeling highly complex, high-stakes data
  • building reliable pipelines and services
  • systems that support AI and agentic workflows