LOAN APPLICATION/DEFERRAL PROCESSING•Leveraged Spark, Hive , Airflow, integrating data from diverse sources, reducing loan processing latency from 24 hours to 4 hours.•Implemented a robust system utilizing Spark and HiveQL to filter ambiguous records, improving data integrity and accuracy by reducing data quality issues from an average of 30 per week to 3-4, marking an 87% improvement.•Led the migration of 50+ TB data to AWS, optimizing storage efficiency through file format conversion and compression, resulting in a 40% reduction in monthly compute costs.CONTACT CENTRE - CUSTOMER DATA ANALYTICS•Designed and developed scalable Spark data pipelines for a Contact Centre application, leveraging Airflow for batch processing of customer, order, payment, and account data, enhancing operational efficiency of customer care agents by 80%.•Implemented optimizations for Spark jobs, including memory management, workflow investigation, minimized shuffle operations, and partitioning upstream datasets, achieving a reduction in the execution time of hourly batch jobs from 40 to 12 minutes.•Developed ad-hoc reporting solutions with AWS EMR and Hive, tailoring datasets to address 50+ unique business queries, driving a 30% increase in data-driven strategies for marketing and loans team.•Revamped Contact Centre application architecture into a Snowflake schema model for streamlined data retrieval, enabling efficient access to customer data based on various metrics, achieving a notable improvement in data retrieval time from 10seconds to 200milliseconds.

CREDIT EVALUATION• Established ETL pipeline for Credit application utilizing AWS S3, SQS and SNOWPIPE, delivering real-time data ingestion into Snowflake for holistic insights and streamlined decision-making.• Integrated AS400 system data applied Snowflake SQL queries for data quality checks and transformed JSON data into actionable records in denormalized tables for analysts, facilitating historical insights and informed reporting.• Migrated data warehouse architecture from Hadoop Hive on AWS EMR to Snowflake, enhancing query execution speed by 50%, with Spark Scala transformations transitioned to Snowpark.• Enhanced data security using RBAC, Masking Policy, and Encryption using UDFs, implementing a platform-level data governance strategy collaborating with multiple upstream and downstream stakeholders.

•Led the design and development of robust MySQL database architectures for airlines client, achieving optimal performance and scalability for the Rewards module. Improved query execution via APIs from 2 secs to 500 milliseconds, improving website load time and customer engagement.•Implemented normalization techniques and constraints on OLTP MySQL server, eliminating redundancy and ensuring data integrity across customer, flight bookings, and rewards datasets. Reduced data duplication and anomalies by 70% compared to the existing framework.•Collaborated with downstream analytics team to apply strategic indexing, accelerating query performance based on patterns. Contributed to a 50% improvement in database responsiveness on customer-to-rewards mapping and acceptance analysis.• Developed and fine-tuned complex SQL queries, employing optimization techniques such as query rewriting and subquery/CTE optimization. Improved weekly/monthly report generation query performance by 40%.•Utilized stored procedures and functions to encapsulate business logic within the database, promoting code reusability and maintainability. Saved over 30 hours of manual effort per week on repetitive tasks.

Single Page Web App Development - Javascript, Angular,HTML5 , CSSDesigning cross platform and responsive website.RestAPI for CRUD operations - Java , Springboot, Node JS