- Led the development of CloudExpert, a cutting-edge cloud cost optimization tool within the Generative AI ecosystem at Incedo, designing and implementing robust data pipelines to streamline cloud cost data ingestion and processing.- Developed and deployed dynamic APIs on Azure Functions, enabling real-time access to comprehensive cloud cost metrics and expenditure analysis, ensuring seamless integration with frontend applications.- Worked closely with the frontend team to accelerate API and product development, collaborating on debugging, deploying, and optimizing components for enhanced performance.- Enriched existing client data using an enrichment framework by adding new features and modifying existing ones, extracting more meaningful insights to support strategic decision-making.- Created multiple PySpark ETL jobs for a Fortune 500 banking client, ingesting data from various sources into target Hive tables for the Marketing System of Insights (SOI) platform, generating insightful KPI trees.- Developed a POC for an enrichment framework to automate raw data conversion into enriched data, providing actionable insights and contributing to client growth.- Contributed as an offshore data engineer for a specialized US Bank's Data Analytics COE on the Mortgage Analytics project, working on Customer Segmentation, Branch Optimization, and Early Warning systems (Risk Analytics), and received the MAD (Made a Difference) award for exceptional impact.- Assisted a US-based life sciences client in transforming raw data into meaningful information, significantly contributing to their revenue growth by providing valuable data insights.- Demonstrated a strong commitment to continuous learning and adapting to new technologies and methodologies, ensuring the delivery of innovative and efficient data solutions.

• Cleaned and transformed datasets using Pandas and NumPy, improving data quality for e-commerce clients.• Analyzed customer segmentation data with SQL and Python, boosting customer retention by 10%.• Automated reporting with Python, cutting manual effort by 40% and ensuring timely report delivery.• Integrated and streamlined data from various sources, including Google Analytics and SQL databases, simplifying ETL processes for more consistent and accessible data.• Analyzed and interpreted complex datasets to reveal actionable insights, leading to a 25% increase in operational efficiency by utilizing data visualization tools such asTableau and Power BI.