Data Engineer

Autodesk is seeking diverse early-career engineering talent to join our Access domain. This is a strategic initiative focused on building scalable, secure data engineering pipelines.

As an Entry-Level Data Engineer, you will contribute to the development and enhancement of data processing and analytics pipelines. You will cultivate a 'Data Champion' mindset by learning and applying best practices in data quality, reliability, and observability. This role offers the opportunity to tackle real-world data challenges that improve platform reliability, resiliency, and scalability.

We are looking for individuals who are detail-oriented, quality-focused, eager to learn, and passionate about creating impact through data.

Our technology stack includes Hive, Spark, Flink, Presto, Snowflake, Looker, PowerBI, and cloud services on Amazon Web Services, complemented by ecosystem technologies from the Apache Software Foundation. Analytics platforms leverage tools from Snowflake, Google (Looker), and Microsoft (PowerBI).

Minimum Qualifications:

• 1-3 years of experience (including strong internship experience) in data engineering, big data, or data analytics.
• 1+ years of exposure to Spark, PySpark, or distributed data processing concepts.
• Proficiency in Python and/or SQL programming.
• Basic understanding of SQL, data modeling concepts, and data warehousing; Hive or Snowflake exposure is a plus.
• Exposure to ETL workflow tools like Airflow or similar is a plus.
• Exposure to BI tools such as Looker or PowerBI is a plus.
• Exposure to version control (Git) and CI/CD concepts is a plus.
• Familiarity with notebook environments like Jupyter or similar is a plus.
• Understanding or academic exposure to streaming or event-driven systems is a plus.
• Strong learning mindset, problem-solving abilities, and communication skills.
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).