Role Summary
This role focuses on building and optimizing secure data pipelines integrating AWS services and Snowflake to support de-identified data consumption by analytical tools and users.
Key Responsibilities
- Integrate de-identified data from Amazon S3 into Snowflake for downstream analytics.
- Build robust ETL pipelines using Glue for data cleansing, transformation, and schema alignment.
- Automate ingestion of structured / unstructured data from various AWS services to Snowflake.
- Apply masking, redaction, or pseudonymization techniques to sensitive datasets pre-ingestion.
- Implement lifecycle and access policies for data stored in Snowflake and AWS S3.
- Collaborate with analytics teams to optimize warehouse performance and data modeling.
Required Skills
46 years of experience in data engineering roles.Strong hands-on experience with Snowflake (warehouse sizing, query optimization, data sharing).Familiarity with AWS Glue, S3, and IAM.Understanding of PHI / PII protection techniques and HIPAA controls.Experience in transforming datasets for BI / reporting tools.Skilled in SQL, Python, and Snowflake stored procedures.Skills Required
S3, snowflake , glue , Iam, Sql