Data Engineer - ETL/Python (6-10 yrs)

Detailed JD :

AWS Glue :

- Strong hands-on experience with AWS Glue for building, testing, and deploying ETL pipelines.

- Knowledge of AWS Glue Crawlers, Jobs, and Workflows.

- Experience in working with AWS Glue Data Catalog and managing schema metadata.

Snowflake :

- Proven experience working with Snowflake for data ingestion, transformation, and analytics.

- Strong proficiency in Snowflake SQL, including writing complex queries, stored procedures, and user-defined functions (UDFs).

- Familiarity with Snowflake Data Loading and Data Unloading techniques.

AWS S3 :

- Proficiency in working with AWS S3 for data storage, managing S3 buckets, and implementing data storage strategies.

- Experience with AWS S3 lifecycle policies, versioning, and data access management using IAM.

Programming Skills :

- Strong knowledge of Python for writing ETL scripts and data transformation tasks in AWS Glue.

- Familiarity with SQL for querying and managing data in Snowflake and other databases.

Cloud & Data Warehousing :

- Solid understanding of cloud technologies, specifically AWS and Snowflake data warehousing.

- Experience with data modeling, data transformations, and best practices for working with cloud data platforms.

ETL Process :

- Hands-on experience in developing ETL pipelines and automating data workflows.

- Ability to design and optimize ETL jobs for large-scale data processing.

Data Security & Governance :

- Understanding of data governance, data quality, and security protocols in cloud-based environments.

- Familiarity with AWS IAM and best practices for securing data access in cloud environments.