Description

You will design and implement scalable data products, pipelines, and frameworks for high-volume data processing across supply chain and commerce domains.

Responsibilities

• Design and build distributed data processing pipelines using AWS, Snowflake, and Dynamo DB.
• Develop data acquisition strategies and profile data to ensure scalable, high-quality solutions.
• Implement complex automated routines and workflow orchestration using Airflow.
• Translate backlog items into engineering designs and define logical units of work.
• Troubleshoot data issues, perform root cause analysis, and improve data quality.

Required Skills

• 10+ years of experience in computer-related occupations with a Bachelor's or Master's degree in CS, CIS, or Information Management.
• Proficiency in Python, PySpark, and SQL for data engineering tasks.
• Hands-on experience with AWS services, Snowflake, and Dynamo DB.
• Experience building data pipelines and using Airflow for orchestration.
• Ability to define and adhere to engineering best practices and continuous integration frameworks.
• Experience with Splunk for monitoring and troubleshooting.
• Strong understanding of data modeling, architecture, and performance profiling.

Preferred Skills

• Experience collaborating with product owners, data analysts, and business partners.
• Familiarity with supply chain, commerce, or web analytics data domains.

Key Skills

Education

Bachelor's or Master's degrees