Description

You will design and implement scalable data architectures to support enterprise data warehousing and analytics.

Responsibilities

• Design and implement scalable Snowflake data architectures for enterprise warehousing.
• Optimize Snowflake performance using advanced tuning and warehousing strategies.
• Develop and manage robust data pipelines using Python and DBT, including modeling and testing.
• Architect and manage AWS data solutions leveraging S3, Redshift, Lambda, Glue, EC2, and IAM.
• Orchestrate and monitor complex data workflows using Apache Airflow DAGs.

Required Skills

• 15+ years of hands-on experience in Data Engineering.
• Advanced experience with Snowflake, including performance tuning and warehousing strategies.
• Expertise in Snowflake security features: RBAC, data masking, and row-level security.
• Proficiency in advanced Python programming for data engineering tasks.
• In-depth knowledge of DBT for data modeling, testing, macros, and snapshot management.
• Strong experience with AWS services: S3, Redshift, Lambda, Glue, EC2, and IAM.
• Extensive experience designing and managing Apache Airflow DAGs.
• Hands-on experience with Apache Spark, Kafka, and Hive, including Hadoop ecosystem knowledge.
• Expertise in SQL (advanced), including PL/SQL and T-SQL.

Preferred Skills

• Experience with Salesforce Data Cloud integration.
• Familiarity with data cataloging tools.

Key Skills

Education

Bachelor's or Master's degrees