Job Summary

We are seeking a seasoned Senior Data Engineer with strong experience solving complex data engineering problems. The project focuses on data transformation and modernization, including migrating from legacy platforms to cloud-enabled modern platforms. Extensive Databricks experience is required, along with strong AWS experience, including S3 and Lambda. Strong Python and PySpark skills are also required. Snowflake experience is a major plus and would make a candidate stand out. The role can be performed remotely; however, an onsite interview is required. The interview process includes a first round via Teams followed by an onsite round, with a technical assessment covering Python, PySpark, and SQL.

Key Responsibilities
• Design and implement data transformation solutions as part of legacy platform modernization initiatives.
• Develop and support scalable data engineering solutions using Databricks and AWS.
• Work with AWS services, including S3 and Lambda.
• Develop data processing and transformation workflows using Python and PySpark.
• Solve complex data engineering and data transformation problems.
• Support migration from legacy platforms to modern, cloud-enabled platforms.
• Collaborate with technical teams to deliver data modernization solutions.

Required Qualifications
• Senior-level experience in data engineering with a strong track record of solving data engineering problems.
• Extensive hands-on experience with Databricks.
• Strong AWS experience, including S3 and Lambda.
• Strong proficiency in Python and PySpark.
• Strong SQL skills.
• Experience with data transformation and platform modernization.
• Ability to successfully complete technical assessments covering Python, PySpark, and SQL.
• Ability to participate in an onsite interview.

Preferred Qualifications
• Experience with Snowflake is a major plus.
• Experience migrating legacy data platforms to modern, cloud-enabled platforms.