As a Data Engineer II at Amazon, I led the organization's mission-critical data platform revamp, spearheading the implementation of a scalable, fault-tolerant solution. I automated job orchestrations using Airflow, enabling seamless scheduling and monitoring of over 50 data pipelines, which resulted in a 50% reduction in pipeline failures. Leveraging AWS CDK, I managed the infrastructure as code, improving deployment consistency and reliability while reducing human errors and accidental modifications.To drive cost savings, I leveraged S3, EMR, and Redshift for efficient data transformation and storage, achieving a 40% reduction in infrastructure expenditure. Recognizing the importance of data quality and integrity, I incorporated a proactive reconciliation framework to ensure end-to-end data reliability. Additionally, I engineered an automated ticketing system that generated up to 50,000 tickets daily using a cost-effective AWS architecture, eliminating 100% of manual efforts and facilitating real-time issue identification for data center teams globally.Demonstrating my technical leadership, I developed a comprehensive data model by integrating and analyzing 15+ disparate data sources. This enabled cross-functional teams to compare Amazon's product catalog against key competitors in the U.S. and EU regions, accessing insights 80% faster and reducing data discrepancies by 90%. I also mentored a team of 3 junior data engineers, fostering best practices in code quality and operational excellence, while actively contributing to the team's technical and business strategy.

During my time as a Data Engineer II at XANT, I demonstrated my expertise in designing and implementing impactful data solutions. I spearheaded the development of a recommendation application tailored for sales representatives, leveraging job function and title data from a database of 150 million customers. This solution resulted in a 40% increase in conversion rates through the delivery of highly personalized recommendations to sales reps.As a lead data engineer, I also drove a significant cost-saving initiative by migrating extensive transactional data from AWS Redshift and Athena to the Snowflake platform. This migration resulted in annual savings of $100,000 by removing the dependency on AWS Redshift clusters for data processing and storage. To optimize the infrastructure expenditure further, I utilized PySpark for streamlined ETL processes, empowered ad-hoc querying on S3 using Athena, and orchestrated seamless data refreshes through Airflow.Collaborating closely with cross-functional teams, including sales, marketing, and product, I translated complex business requirements into scalable, efficient data engineering solutions. I also provided technical expertise and guidance to junior data engineers, contributing to their professional development and the overall capabilities of the team.

As a Data Mining Analyst Intern at the University of Utah, I had the opportunity to leverage my skills in natural language processing (NLP) and data analytics to enhance the student experience on campus. I conducted sentiment analysis on the university's technical and cultural events, utilizing NLP techniques to extract valuable engagement metrics. This enabled the university's IT and marketing teams to gain deeper insights and make data-driven decisions to improve event planning and student engagement.To support this initiative, I developed Python-based data pipelines to ingest, process, and analyze structured and unstructured data from various sources, including event registration systems and social media platforms. Collaborating closely with the stakeholders, I identified key insights and presented data-driven recommendations that directly impacted the student experience.This internship experience allowed me to apply my data mining and machine learning expertise to solve real-world problems in an academic setting. I gained valuable hands-on experience in translating complex data into actionable insights, further strengthening my ability to deliver data-driven solutions that make a meaningful impact.

During my tenure as a Data Engineer at Paytm, I demonstrated my expertise in architecting scalable, high-performance data solutions to support the company's rapidly growing business. I engineered a Spark-based application framework that enabled the seamless integration of reporting, facts, and OLAP jobs, facilitating the automated delivery of over 50 business-critical data views and reports on a daily basis.To ensure the scalability and reliability of Paytm's data infrastructure, I designed fault-tolerant big data pipelines to batch process data from diverse sources into a centralized AWS data lake. I orchestrated the data inflow by defining the data layer for the UPI payment gateway, managing over 130 million transactions monthly while maintaining 100% compliance with privacy regulations.Furthermore, I played a crucial role in Paytm's data privacy and compliance efforts by implementing a comprehensive PII data masking solution using PySpark, Hive, Python, and SQL. This solution protected the information of 100 million customers, safeguarding the company from quarterly government audits and ensuring the highest standards of data security and privacy.Through my innovative data engineering solutions and commitment to data integrity, I was able to make a significant impact on Paytm's data capabilities, enabling the organization to scale its operations and maintain compliance with industry regulations.

At EasyRewardz Software Services, I leveraged my expertise in Spark and big data technologies to architect a scalable, automated campaign management system. By harnessing Spark's powerful data processing capabilities, I was able to read and analyze a customer database of 150 million individuals, identifying targeted segments based on specific parameters such as upcoming birthdays.I then developed a system that automatically triggered personalized marketing campaigns for these targeted customers, driving a 35% boost in profits through increased customer engagement and campaign effectiveness. This solution streamlined the entire campaign management process, eliminating manual efforts and enabling the marketing team to deliver timely, personalized outreach at scale.Additionally, I was able to demonstrate the financial impact of this data-driven approach, lowering marketing costs by approximately 20% compared to the previous blanket campaign strategies. Through my innovative Spark-based solution, I empowered the organization to execute highly targeted, personalized campaigns that yielded substantial business results.This experience showcased my ability to translate complex business requirements into scalable, data-driven solutions that drive tangible impact on the bottom line. It further demonstrated my expertise in leveraging big data technologies to enable data-powered decision-making and optimization within the organization.

As an Assistant System Engineer at Tata Consultancy Services, I demonstrated my versatility by delivering both data engineering and enterprise software development solutions. In one of my key projects, I developed an Enterprise Resource Planning (ERP) system for a government entity, enabling digital bookkeeping and streamlining their financial operations.Leveraging Java and SQL as the backend technologies, I designed and implemented a scalable, user-friendly ERP application that addressed the client's specific requirements. Collaborating closely with the stakeholders, I ensured the delivered solution improved data management, reporting, and overall operational efficiency for the government organization.Concurrently, I also established a centralized data store utilizing big data technologies to manage the company's customer information. To optimize this data infrastructure, I engineered efficient ETL pipelines for data processing and migration from legacy systems, achieving a 40% cost reduction through minimized data scan and compute size.This experience showcased my ability to tackle diverse challenges, from building enterprise-grade software applications to designing scalable data solutions. By demonstrating my technical expertise across multiple domains, I was able to drive meaningful business impact and operational improvements for the organization.