Principal Software Engineer, Product Analytics

Position Overview 

Do you thrive in a fast-paced, high-energy environment? Are you a creative problem solver who enjoys building and optimizing infrastructure using cutting-edge technologies? Are you looking to collaborate with motivated individuals from diverse backgrounds? Do you have the drive to make things happen? If so, you are in the right place. 

As a global leader in 3D design, engineering, and entertainment software, Autodesk helps people imagine, design, and create a better world. Autodesk enables better design through an unparalleled depth of experience and a broad portfolio of software to give customers the power to solve their design, business, and environmental challenges. In addition to designers, architects, engineers, and media and entertainment professionals, Autodesk helps students, educators, and casual creators unlock their creative ideas through user-friendly applications. 

The Experience Analytics Team is a centralized Analytics team working closely with product line development teams across the company to democratize ML/Analytics across all Autodesk products. You will be working on a myriad of analytics related to a data product that provides ML insights to AutoCAD users. We help those teams with all their internal and customer-facing Analytics needs by way of instrumentation, experimentation, reporting, analysis, in-product analytics, and machine learning. We are looking for technically savvy DevOps engineers with a passion for infrastructure and automation who are eager to help us bring data-driven thinking into day-to-day product engineering practices. We are seeking individuals who are attracted by complicated problems, who can think creatively, and work hard to help us solve them. 

Have a sneak peek into the innovation we are working on: 

• AWS Case Study 

• My Insights AutoCAD Overview 

• Autodesk Product Insights <> MongoDB 

If you are a highly motivated DevOps engineer with a passion for building and optimizing infrastructure and want to work in a dynamic and collaborative environment, we encourage you to apply. Join us in our mission to democratize ML/Analytics across all Autodesk products and help shape the future of design and engineering. 

Responsibilities 

• Infrastructure Management: Build and manage scalable infrastructure for data scientists and analysts

• Automation: Develop automation tools for deploying and managing infrastructure

• CI/CD Pipelines: Create and maintain continuous integration and continuous deployment pipelines using AWS CI/CD technologies such as AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy

• Monitoring and Alerting: Implement and maintain system monitoring and alerting solutions

• Collaboration: Interface with data scientists, analysts, product managers, and all data stakeholders to understand their needs and promote best practices

• Optimization: Optimize performance and ensure high availability of infrastructure and services

• Security: Ensure the security of the infrastructure and data

• Agile Methodology: Work in an Agile environment that focuses on collaboration and teamwork

Minimum Qualifications

• Education: BS or MS in Computer Science or a related field, and 5+ years of professional experience

• Database Experience: Strong experience with databases (RDBMS, MongoDB, DynamoDB)

• Automation and Configuration Management: Experience with tools such as Terraform, Ansible, or Puppet

• Cloud Platforms: Experience with cloud platforms, particularly AWS

• Scripting and Programming: Working knowledge of scripting and programming languages (Java, JavaScript, bash, Python preferred)

• CI/CD Tools: Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI, and AWS CI/CD technologies (AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy)

• System Monitoring: Experience with system monitoring tools (e.g., Prometheus, Grafana) and dashboarding

• Production-level Coding: Production-level coding experience

• Big Data Environments: Experience working with big data environments such as Hadoop (Hive, Spark)