• Hands-on experience designing and developing relational database models and datasolutions using various cloud data warehouses, such as Snowflake, Databricks,Teradata, as well as integrating with data lakes to enable scalable data processing.• Designed and implemented scalable data pipelines using advanced ETL/ELTmethodologies, optimizing data flow across complex enterprise environments whileadhering to best practices for scalability and self-healing approaches.• Proficient in data warehouse concepts, including star, snowflake, and dimensionalmodeling, with a strong focus on implementing solutions that ensure scalability andefficient process management.• Understanding and practical experience with big data architectures, including Lambda,Hub-and-Spoke, to design robust, real-time, and batch data systems.• Worked on data governance and data security initiatives to ensure compliance and dataintegrity.• Incorporated data quality checks using Great Expectations, SQL, and monitoringdashboards, ensuring robust reconciliation between various systems.• Built data visualizations and crafted narratives using tools like Tableau and Looker,enabling effective decision-making.• Extensive experience leveraging quantitative analysis, experimentation, and predictiveanalytics to uncover opportunities, drive strategic business decisions, and deliverperformance insights.TECHNICAL EXPERTISE• Languages: SQL, Python, PySpark, Spark Streaming• Data Warehouses: Snowflake, Databricks, Teradata, PostgreSQL• Data Lake Tools: Apache Iceberg, Delta Lake• Tools/Servers: Terraform, Git, REST APIs, Jenkins, SQL Developer, Linux• Data Visualization: Tableau, Looker• Cloud Platforms: AWS (Redshift, S3, Glue, IAM, EC2)• Scheduling/Workload Automation: Airflow, Autosys• Infrastructure as Code: Terraform• Messaging Queue: KafkaBUSINESS SYSTEMSNetSuite, Zuora, Salesforce, Recurly and Coupa