Shruthi DN

Client: Sanofi (CHC, BioPharma), Regeneron

DATA & AI ENGINEERING / DATA QUALITY PLATFORM (DATAORION)

1. Built DataOrion, an AI-powered data platform on Snowflake enabling automated, end-to-end AI-ready data preparation.
2. Developed LLM-driven metadata generation (BMG) integrated with Informatica CDGC using Snowflake cortex.
3. Designed Qualii, an AI-based Data Quality engine for natural language → SQL rule generation, LLM-driven, combining metadata, sample data, and user context.
4. Engineered scalable pipelines using Snowflake, Python, Streamlit, enabling agentic workflow orchestration.
5. Implemented config-driven DQ framework (EDG-DQ) supporting in-motion & at-rest validation.
6. Built SQL-based rule engine, error logging, and failed-record tracking for enterprise datasets.
7. Automated DQ score computation & publishing to CDGC, improving governance and catalog insights.
8. Integrated pipelines with Informatica CDI/IICS for orchestration and scheduling.
10. Built Streamlit UI + backend services for rule generation, deduplication, and SQL normalization.
11. Integrated Snowflake Cortex models for intelligent rule recommendations.

AWS SERVERLESS DQ & ANALYTICS

1. Built serverless DQ Score Utility (AWS Lambda, API Gateway, DynamoDB, S3, SNS).
2. Developed API-driven DQRO processing (GET/POST) with CDGC integration.
3. Implemented secure APIs (OAuth2/JWT via Layer7) and job tracking with DynamoDB.
3. Automated deployments using Terraform + GitHub Actions (CI/CD).
4. Engineered serverless pipelines for structural DQ checks integrated with Informatica ingestion flows.

POWER BI DATA QUALITY DASHBOARD

1. Built enterprise DQ dashboards using Snowflake + Power BI for real-time insights.
2. Developed KPIs, DAX, and data models for DQ score tracking and trend analysis.
3. Implemented RBAC and reusable templates for scalable deployments.

Client: TERADYNE

MELISSA ADDRESS VALIDATION

1. Built batch address validation pipeline using Melissa API (Python + Snowflake).
2. Implemented parallel processing, batching, and caching for performance optimization.
3. Mapped Melissa codes (AE/AC/AV/AS) into structured outputs
Built dynamic validation classification (Verified, Partial, Failed)
4. Enabled address standardization with error handling and retries

Provided expert consulting services to optimize client technology infrastructure.

• Provisioned tech infrastructure, validated tech infra, and set up development environments for VDI and infra access
• Tech infra provisioning, VDI and Infra Access, Validation of Tech Infra, Development Setup
• Tracked project activities and facilitated client-facing calls to ensure alignment and address concerns
• Started learning Pyspark and Azure Data Factory for data processing tasks.

• Created DataLake, Designed and developed AWS serverless ETL Pipelines for Operational Analytics dashboards on PowerBI.
• Served as Scrum master, created and assigned Jira tasks to development team of 7 members to streamline project workflow.
• Implemented automation of manual reports being generated by internal teams replacing the manual effort of 40 hours per week that reduced cost.
• Implemented centralized repository for SQL server agent jobs metadata and job statistics and System performance metrics from On-Premises servers and helped Power BI team to implement the dashboard
• Managed CI/CD deployments using Git, Bitbucket, Jenkins on EC2 and Terraform to ensure smooth release processes.
• Conducted training sessions & mentoring to fresh recruits from university and to upskill existing team members on SQL and AWS Data Analytics services
• Established centralized repository for SQL server agent jobs metadata, job statistics, and system performance metrics from on-premises servers, supporting Power BI team's dashboard implementation.

• Developed design documents, ETL design specifications, and data models (LDM/PDM) to support ETL processes.
• ETL Development using SSIS (Domain: Automobile), Informatica (Work and Pension) and SQL.
• Prepared the test strategy document
• Conducted unit testing and supported system integration testing, developed and unit tested functionality based on design specifications, and migrated data from IDIT system to GENESIS system using DB2.
• Worked on detail design documents, DBRs (Detailed Business Requirements)
• Analyzed defects in TSRM.
• Participated in build and deployment phases for creating packages in RTC and conducting smoke tests.