Developed and implemented a scalable marketing data warehouse, dashboards, and data insights using data ingestion/transformation systems built in-house primarily on SQL Server, AWS, Snowflake.
Orchestrated Python and SQL based big data pipelines (Hive, Presto, Spark) using Kubernetes, Docker, Airflow and utilized continuous integration using Terraform, Jenkins, Git that enabled self-service reporting.
Worked closely with business and data science teams to productionize their statistical ads models such as First / Last touch attributions, Multitouch attributions for Salesforce Campaign Performance Reports.
Ensured proper source control, documentation, Unit Test, and established quality assurance processes, implemented, and followed to maintain high data integrity and data governance.
Led the end-to-end ownership of data integration and reporting solutions for billing, invoicing, Salesforce, and finance teams, implementing SOX and GDPR compliance and other operational workflows for BI projects.
Defined and managed SLA for data sets in allocated areas of ownership and implemented Correction of Errors (CoE) actions based on business requirements.
Tools: SQL Server, SSIS, SSRS, SSAS, Teradata, Airflow, PyTest, Snowflake, S3, Redshift, Looker, Tableau, Power BI, Fivetran, Jira, Git, Salesforce, Azure Data Lake, Jinja, PUTTY, Oozie, Oracle, Postgres