Job Requisition ID #

25WD84745

Position Overview

Autodesk is looking for diverse engineering candidates to join Licensing and Compliance team, a collection of systems and teams focused on detecting and exposing non-compliant users of Autodesk software. This is a key strategic initiative for the company!

As a Principal Data Engineer, you will be responsible for developing best practices and making architectural decisions to rapidly improve critical data processing & analytics pipelines. You will tackle hard problems to improve the platform's reliability, resiliency, and scalability.

We are looking for someone who thrives on autonomy and has experience driving long-term projects to completion. You are detail and quality oriented, and excited about the prospects of having a big impact with data at Autodesk. Our tech stack includes Airflow, Hive, EMR, PySpark, Presto, Jenkins, Snowflake, Datadog and various AWS services.

• Modernizing and expanding a critical set of existing systems
• Understand business requirements and architect systems that will scale and extend to accommodate those needs
• Break down complex problems, document technical solutions and sequence work to make fast, iterative improvements
• Build and scale data infrastructure that powers batch and real-time data processing of billions of records
• Develop CI/CD ETL pipelines using Jenkins for deployment and automation testing
• Take ownership of ETL pipelines, own data quality for your areas, and ensure SLAs are met
• Interface with data engineers, data scientists, product managers and all data stakeholders to understand their needs and promote best practices
• Lead the design and implementation of complex data processing systems, ensuring they meet business requirements and performance standards
• Manage and coordinate the efforts of a team of data engineers, ensuring alignment with project goals and timelines
• Provide technical guidance and mentorship to junior engineers, fostering a culture of continuous learning and improvement

• 9+ years of relevant industry experience in big data systems, data processing and SQL data warehouses
• At least 5+ years of experience on working with large Hadoop projects and building scalable applications using PySpark by leveraging Spark DataFrame and Spark SQL api.
• At least 2+ years of experience in optimizing Spark applications, spark memory management, and e2e spark process optimization
• Strong overall programming skills, able to write modular, maintainable code, preferably Python & SQL
• Fundamental knowledge of distributed data processing systems, storage mechanisms, and compression techniques.
• Experience building code-driven infrastructure on public cloud platforms, preferably AWS
• Understanding of SQL, dimensional modeling, and analytical data warehouses, like Snowflake, Redshift
• Knowledge of Data Modeling techniques and high volume ETL/ELT design.
• Familiar with workflow management tools, like Airflow and Oozie
• Experience with CI and code management tools like Git, Jenkins
• Familiar with BI tools, like Power BI, Looker, Qlikview
• Problem solver with excellent written and interpersonal skills; ability to make sound, complex decisions in a fast-paced, technical environment
• Bachelor's degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience
• Product-focused mindset