Building Advanced Data Pipelines with Snowflake and AWS

• Execute OAuth and REST API calls to acquire client data in JSON format.

• Develop Python scripts for data extraction and categorization into cloud storage for incremental and full load using cloud infrastructure and Big Data Hadoop.

• Manage code base on GitHub, ensuring proper version control and documentation in Confluence.

• Establish Fivetran connections to facilitate ETL processes from buckets to cloud Data Warehouse.

• Collaborate on data transformations within Snowflake, optimizing query performance for analytics.

• Utilize DBT for efficient data modeling and transformations in both Dev and Prod environments.

● Designed, built, and launched new data pipeline ingestion in Enterprise Data Warehouse, mentoring others around efficient Python ETL implementation, Data Quality checks and Unit Test reducing job failures and deployment failures by 50%.

● Defined and managed SLA for all data sets in allocated areas of ownership, providing technical documentation, data flow diagrams, version control standardizing intake processes.

● Worked with product and finance teams to develop models for spend attribution to ads performance, clicked bookings, exposed bookings to support advertiser billing reports and campaign performance reporting.

● Participated in on-call rotations, responded to ad hoc data requests, and conducted analysis to provide valuable insights to partner groups, including sales, product, operations, and finance.