Engineer 3, Data Engineering

Design, develop, and optimize enterprise-scale data pipelines and scalable cloud data platforms on AWS using Python, PySpark, and services like S3, Glue, Athena, Redshift, Lambda.

Implement data governance, quality, metadata management, and lineage frameworks to ensure trusted, high-quality enterprise data compliant with privacy and regulatory standards.

Collaborate with stakeholders to define and promote governance standards, lead technical mentorship, and drive operational excellence through automation and continuous improvement.

5-7 years of experience in Data Engineering, Data Platform Engineering, or related fields.

Strong hands-on skills with Python, PySpark or Apache Spark, SQL development, and AWS data services (S3, Glue, Athena, Redshift, Lambda).

Practical experience implementing data governance, metadata management, data cataloging, and data lineage.

Bachelor's degree preferred; relevant combination of coursework and experience may be considered.

Experienced in building and optimizing large-scale, cloud-based data pipelines and platforms with a strong focus on governance and compliance.

Skilled in collaboration across diverse technical and business groups to implement and standardize data governance and quality frameworks.

Proven ability to lead technical reviews, mentor peers, and contribute to the growth of data engineering teams in complex, regulated environments.