• Led the integration of client data through API ingestion using Microsoft Azure Functions and Azure Data Factory to bring on-premise data into the cloud• Developed and implemented unify logic in sql for each customer to standardize their data format, aligning it with the system's predefined structure• Investigated and resolved data mismatch issues between system values and customer data using databricks notebook, enhancing data accuracy and reliability

As a Data Analyst at Retailo, I took several pivotal initiatives aimed at enhancing operational efficiency, financial accuracy, and data reliability across the organization:• Financial Reporting Enhancement: Implemented innovative SQL logic to refine last-mile cost allocation procedures, optimizing warehouse and storage cost calculations. Additionally, integrated inventory shortages into financial reporting processes, resulting in 25-27% improvement in the accuracy of Profit and Loss (P&L) reporting.• Cash Conversion Cycle Visibility: Created a sophisticated Cash Conversion Cycle dataset in SQL, offering granular insights at the vendor, location, SKU, and purchase order levels. This initiative facilitated more effective cash flow management strategies.• Data Integration Reliability Enhancement: Leveraged Python and AWS Lambda to develop an automated Airbyte job failure slack bot, revolutionizing the detection of data integration failures. This solution significantly enhanced data reliability and minimized downtime, ensuring seamless operational continuity.• Workflow Efficiency Enhancement: Streamlined dbt workflows in Argo by implementing strategic modifications to the re-run policy, focusing on failed and skipped models exclusively. This initiative led to an impressive 80% reduction in workflow failure rates, significantly enhancing operational efficiency.• Data Transformation Automation: Developed Python script utilizing AWS CloudTrail and QuickSight via Boto3 to query and transform of data. This initiative enabled the identification of unused analyses and streamlined data preparation processes, thereby enhancing overall efficiency and accuracy.• Excel to CSV Automation: Engineered a Python script to automate the transformation of Excel files into CSV format, eliminating the need for manual file creation. This streamlined the process of preparing data for input into a SaaS product, significantly improving efficiency and accuracy in data processing.