Demonstrated experience with SQL.
Demonstrated experience with Python.
Demonstrated experience with PySpark.
Demonstrated experience with T-SQL.
CVS Health
Engineered scalable data pipelines using Python and PySpark on AWS Glue and Databricks to process millions of customer records daily, supporting personalized marketing outreach across regions., Migrated legacy marketing tables into Snowflake, employing dynamic partitioning and clustering strategies to reduce query latency by 40% and improve dashboard responsiveness for key business stakeholders., Designed and maintained a centralized master customer model incorporating CRM hierarchies, consent preferences, channel behaviors, and opt-out history for downstream analytics and targeted outreach programs., Implemented HIPAA and GDPR-compliant pipelines with audit trails, field-level data masking, and consent-based filtering logic for regulatory alignment across data ingestion and activation workflows., Developed reusable deduplication and fuzzy match logic in PySpark, integrating consent validation frameworks to enforce communication frequency rules and eliminate redundant or non-compliant records., Created Power BI dashboards to track campaign reach, conversion rates, opt-out metrics, and regional performance insights, promoting self-service analytics across cross-functional marketing stakeholders., Led Agile ceremonies including stand-ups, sprint reviews, and retrospectives to plan, prioritize, and deliver enhancements to marketing data infrastructure and campaign enablement products., Tuned ETL jobs for performance and cost efficiency in AWS Glue, reducing failure rates and enabling responsive ad-hoc query support across multiple analyst and reporting teams., Integrated CI/CD pipelines for AWS Glue and Databricks using Azure DevOps, enabling seamless, version-controlled deployments and rollback support across marketing data platform components., Contributed to the design and implementation of a federated data validation framework to monitor potential data inconsistencies across various data sources and pipelines.
HDFC Life Insurance
Consolidated CRM and compliance data to create master datasets for customers, agents, and policyholders, enabling unified reporting, segmentation, and audit-ready reference tables for business analytics., Designed ingestion workflows using Apache Airflow to integrate PostgreSQL, call center feeds, and campaign management tools, ensuring reliable, scalable, and traceable customer data pipelines., Implemented rule-based validations and metadata tagging to flag incomplete records, consent mismatches, and duplicate entries, improving downstream data quality and compliance adherence., Collaborated with legal and marketing teams to enforce GDPR, IRDAI, and internal governance policies, embedding compliant logic into transformation pipelines and campaign segmentation workflows., Created Tableau dashboards to visualize renewal trends, agent productivity, customer conversions, and early churn indicators, supporting executive decision-making and operational strategy., Engineered enrichment processes in Python to calculate policyholder engagement scores, churn likelihood, and upsell potential using behavioral, demographic, and historical interaction data., Reduced ETL latency by tuning PostgreSQL queries, implementing incremental loads, and optimizing Airflow DAG execution schedules to support frequent campaign refreshes., Proposed and documented architecture to transition on-premises lakehouse workloads to GCP using BigQuery, GCS, and secure data exchange policies for future scalability., Gained familiarity with SQL tuning techniques to optimize query performance in PostgreSQL, contributing to faster data retrieval and improved overall system efficiency., Contributed to building scalable data pipelines for integrating diverse data sources, ensuring data privacy and security through best practices and adherence to data governance policies.
Master's
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Demonstrated experience with Shell Scripting.
ICICI Bank
Developed SQL-based ETL jobs to process daily and weekly transactional, CRM, and channel performance data, populating centralized data marts used for executive reporting and customer insights., Migrated over 30 Excel reports into Power BI dashboards with interactive filters, historical trend views, and drill-through capabilities for KPIs, enabling scalable and visual self-serve reporting., Created logical data models to group accounts by household, branch, and banker relationships, improving customer segmentation and territory alignment for personalized outreach and performance monitoring., Designed persona generation logic using channel preference, geography, and transaction frequency to enable targeted campaign execution and regional marketing optimization., Collaborated with Salesforce administrators to align CRM data fields with Power BI visualizations, improving accuracy of customer performance views and frontline tracking dashboards., Wrote stored procedures and materialized views in SQL Server to power executive scorecards with daily, monthly, and quarterly updates across business performance verticals., Standardized KPI definitions and reusable filter logic across dashboards to ensure consistent views between compliance, product, and frontline teams in business performance reviews., Conducted training workshops for over 40 branch leads on using Power BI dashboards, interpreting KPIs, and leveraging self-service filters for daily performance monitoring., Gained experience in data warehousing concepts by building and maintaining data marts, ensuring data privacy and security through appropriate access controls and data masking techniques., Contributed to the development of scalable data pipelines for integrating various data sources, ensuring data quality and adherence to data governance policies throughout the ETL process.
