• Led a team in developing a scalable and efficient data pipeline for Clinical Lab Results, ensuring seamless data ingestion from multiple CLV’s (Clinical Lab Vendors), validation, and processing using AWS services like Lambda, Glue (Pyspark), Event Bridge, and Aurora PostgreSQL, S3, IAM. Improved operational efficiencies and reduced cycle time by ensuring effective cloud implementation.• Orchestrated AWS Step Functions to automate workflows, enhancing the performance and reliability of data pipelines, while implementing encryption for data security during transit and storage in S3.• Performed anomaly detection for Lab test Clustering, Outlier timestamps, and warnings on acute lab results with cross verification with LRT’s.• Managed vendor evaluations, external partnerships, and procurement processes, ensuring the selection of optimal solutions for business needs.• Conducted performance optimization, end-to-end testing, and regular architectural assessments, identifying opportunities for improvement and driving future business capability.• Designed and developed data pipelines for processing Clinical Trial Master and Reference data, implementing data lake and warehouse architectures on AWS.• Ingested data from AWS S3 to Aurora using Lambda and event triggers, while managing orchestration with Step Functions.• Migration of on-premises Oracle databases to AWS RDS Database using AWS DMS services and setting up the continuous replication of ongoing changes.• Creating Data Pipelines using Glue and Python to perform ETL Operations. • Migrated on-prem Oracle tables to AWS Aurora using Glue ETL jobs, integrating AWS services like Lambda, SNS, SES, and Step Functions.• Collaborated with cross-functional teams, mentored junior members, and conducted knowledge-sharing sessions.• Created comprehensive documentation for data pipeline governance and aligned technical solutions with business goals through stakeholder communication.

Industry/ Vertical - Pre- Clinical R&D (Pharmaceutical)XLIMS - Custom LIMS, Covid-19 Sample data management.Solution owner for a strategic initiative aimed at creating custom cloud-based LIMS application and replace Waters LIMS for clinical lab results. This solution has following features:- Sample Management- Complete Storage management.- Integrated Instrument Management.- Dynamic access management.- Multi vendor/Lab support.- Sample Assay- PRF Results- Data Analytics and Dynamic reporting.- 21 CRF part 11 compliant.Add ons -- Dynamic reporting capability.- Master data Management.- Reduced turnaround time for PRF form creation.- Multi-Lab support.- Barcode scanning of Code 128, Data Matrix, and Quick Response (QR) Codes. • Technical solution discovery for complex LIMS system that involve putting together low level detailed technical designs. • Establish low level detailed technical architecture for LIMS implementation.• Responsible for Physical and Logical Data Model creation.• Responsible for decomposition of requirements into epics & stories, estimation, and assigning work to team members.• Manage client deliveries and expectations for LIMS alongside internal deliveries.

• Led the implementation of Informatica MDM to manage Site, Site Personnel, Compound, and Reference Data, establishing a single source of truth, ensuring data consistency across systems.• Created a custom data stewardship interface in Informatica Data Director (IDD) for managing and authorizing master and reference data, automating the validation process, matching, and approval processes, resulting in a 20% reduction in manual intervention.• Utilized Informatica Data Quality (IDQ) to profile, cleanse, and validate data, ensuring high accuracy and consistency, resulting in a 30% improvement in data accuracy.• Defined match and merge rules, user exits, trust matrix, match paths, and match criteria.Team Lead (ETL/Informatica Developer) Data Integration Platform (Clinical R&D) | Indianapolis, IN, USA JUL 2015 - MAR 2017• Developed analytical marts in Access layer for risk-based monitoring, resulting in ~5% reduction in the time required to bring drugs to market.• Orchestrated near-real-time data integration, covering eDC Results, Lab Results, Subject Enrollment.• Designed/created processes such as Visit & Subject reconciliation, Reference Data flow across layers.

Industry/ Vertical - Pharmaceutical, Clinical R&D• Helped Setup Data Privacy Office at client site by creating Data Classification Documents and Data Anonymization needs for the unit.• Conducted meticulous review and testing of study protocol documents using SDTM standards, and proposing strategic amendments.• Developed custom system for de-identifying and scrambled sensitive data from diverse source systems (Clintrial, Eclinical, Impact, eCTS, and GLS, CLRM, Denodo) which facilitated comprehensive testing of the entire data warehouse with a large and robust dataset while adhering to FDA guidelines and ensuring HIPAA compliance.• Created Methodology documents to onboard multiple other systems on test data platform and utilize similar algorithms.

• Enhancement and maintenance of Eclinical, Clintrial, Clintrial Integration Solution, GLS Integration, MedDRA Integration, WHO drug Integration, Clintrial Extract to Climate, J-Review, Inform, and Grants Integration.• Implemented Six Sigma methodologies for the investigator payments, achieving an annual saving of $1.6 million by eliminating overpayments.

Industry/ Vertical - Insurance• Business Requirements elicitation use case analysis, data analysis, and developed functional design specifications.• Responsible for functional Analysis and logic/workflow designing of different modules.• Providing support for IUT (Integration Unit Testing), System Testing, Regression testing & post-production.

NLP Engineer and Data Scientist | Discerning Organizational Identities• Fine-tuned BERT Zero-Shot for Text Classification on the philanthropic data (Form-990 fillings) of foundation grantee network of the entire US non-profit sector to develop a custom trained model.• Utilized K-Means clustering in scikit-learn to label a large unlabeled dataset to prepare for classification, supervised learning model training.• Integrated Open API for efficient and experimental religion classification in religious organization data. Additionally, pioneered NLP Tree-of-Thought Prompt Engineering techniques for Large Language Models (LLMs) to perform binary and multi-class classification, providing generative recommendations within US non-profit sector Form-990 filings.Data Engineering and Visualization | Foundation and Grantees Network• Created a robust architecture with data cleaning and processing routines for technical and non-technical access on Form 990 data.• Designed and created intuitive Tableau Dashboards for Grants Network, and respective profiles of Grantees and Foundations. This was crucial for Sponsor to get further funding for the project.