AbbVie

• Ensured data integrity by reducing ETL process failures by 40%, through diligent monitoring, analysis, and resolution, impacting the accuracy of healthcare analytics.
• Achieved a 30% improvement in data processing speed by optimizing queries with Spark's Adaptive Query Execution and broadcast joins, enhancing efficiency in large-scale data operations.
• Provided critical support and strategic recommendations to AbbVie's stakeholders, improving project implementation effectiveness in the VEEVA safety domain by directly collaborating with client teams..
• Increased offshore team productivity by 25% by mentoring a team of 3, leading code reviews, and facilitating technical sessions, thereby elevating project delivery standards.
• Designed and managed database schemas for Power BI reporting, enabling advanced analytics for 300+ business users, which supported strategic decision-making through enhanced data visualization.
• Operated within a tech environment comprising Cloudera, Scala, Shell Scripting, ETL, and Git, showcasing adaptability and proficiency in leveraging technology to drive project success.

Sr. Data Engineer

TEKSOLVE IT SOLUTIONS LLC

• Developed and managed an ETL pipeline to process over 140GB of data daily, utilizing web scraping APIs and Airflow orchestration, enhancing data availability and reliability for banking analytics.
• Optimized data extraction from Teradata to HDFS by 25% by implementing advanced Sqoop filtering
techniques, streamlining the data flow process for critical financial transactions.
• Enhanced data integrity and reduced redundancy by transforming transactional data into 30+ facts and dimensions tables using Spark SQL, improving the data warehouse structure for complex analytics.
• Facilitated improved data mapping accuracy by collaborating with cross-functional teams to define source-to-target mapping documents, ensuring reliable data transformations and analytics.
• Improved Hive query performance by 20% through optimized partitioning and data distribution strategies, significantly speeding up data access for time-sensitive financial reporting and analysis.

Data Engineer

Clark University

•	Facilitated weekly 2-hour Q&A sessions with 50 new students to clear doubts and assisted in enhancing their coding strategies.
•	Grades 50+ of assignments of the students enrolled for Linear Regression subject for 2 classes.

Graduate Teaching Assistant

• Designed and deployed ETL pipelines using Spark SQL and Airflow, integrating over 2TB of clinical trials data from diverse sources such as CSV files, APIs, and MySQL tables. This enabled comprehensive data processing for advanced research applications.
• Facilitated data integration by executing API calls via Postman to collect responses in JSON format,
streamlining the initial data collection phase into the S3 staging layer for further processing.
• Developed SQL scripts for an end-to-end data cleansing process, effectively cleaning 2 million records per migration, which significantly reduced data anomalies and improved data quality for migration projects.
• Achieved 100% mapping accuracy between therapeutic areas and diseases across five data sources using Spark SQL, ensuring the reliability of critical healthcare data for analysis.
• Implemented TAMR MDM Tool and deduplication strategies to enhance the mastering of pharma trials, sites, and investigators' data, improving data accuracy by 85% and supporting more reliable research outcomes.
• Employed Python for counterfactual analysis to fill missing values, enhancing KPI Enrollment Duration by 5%. This contributed to a significant improvement in the accuracy and performance of critical performance indicators.
• Standardized data for 27K diseases across five data sources by leveraging TERMite and CENTREE ontologies, increasing disease data accuracy by 60% and enabling more precise disease identification and research.

Big Data Engineer

Wipro

• Designed and implemented scalable ETL pipelines for data integration and processing, utilizing Apache Spark and Apache Airflow, resulting in a 40% increase in data processing efficiency for major projects.
• Managed big data analytics platforms, enhancing data quality and accessibility by integrating various data sources (SQL databases, Hadoop clusters, and cloud storage) into a cohesive data ecosystem.
•Developed real-time data processing solutions using Kafka and Spark Streaming, enabling the analysis of streaming data for immediate insights, which supported critical decision-making processes.
• Optimized data warehouse performance through advanced SQL tuning and schema design, achieving a 20% improvement in query response times, thereby enhancing user satisfaction for analytics applications.

Jr. Data Engineer

Dynamic and detail-oriented Data Engineer with over 5 years of experience in designing, implementing, and maintaining cutting-edge data processing systems. Skilled in crafting scalable ETL pipelines, managing big data technologies, and leveraging advanced analytics to drive decision-making and business insights. Proven expertise in optimizing data architecture, enhancing data quality, and integrating diverse data sources into cohesive and efficient systems.

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