Data Engineer Information Technology

Veer Pradyumna Karadia

*******.*@************.*** 857-***-**** Github LinkedIN

Results-driven Data Engineer/Analyst with 5 years of experience in the customer, marketing, and finance sectors. Proficient in designing and optimizing data pipelines, dashboards, and visualizations to provide actionable insights. Eager to leverage generative AI and advanced analytics to develop innovative, data-driven solutions. EDUCATION

Northeastern University, College of Engineering

Master of Science in Data Analytics (Information Technology) Amity University

Bachelor of Technology in Computer Science Engineering CERTIFICATION

• Azure Data Engineer Associate Certification (Link) 2025-2026

• AWS Academy Cloud Architecting Certification (Link) 2022-2023 EXPERIENCE

Data Engineer, KGS Technology 2024-Present

• Migrated marketing data to Azure Blob Archive, reducing storage costs by 44% while maintaining data integrity and audit compliance

• Built PySpark workflows for RFM segmentation, improved targeting accuracy and increasing event marketing conversion rates by 30%

• Used SSIS to sync CRM and promotions data, pooling customer insights and improving email targeting accuracy by 25% across events

• Established Data Catalog, IAM policies, and VPC-level controls, cutting unauthorized access by 60% and ensuring HIPAA compliance

• Integrated sales data streams into BigQuery via Kafka Connect and Databricks, scheduled with Airflow, boosting engagement by 20%

• Streamlined Event Hub ETL with Kafka, CI/CD, reduced backlog by 50% and accelerated campaign-driven customer insight delivery

• Led streaming platform onboarding, collaborating with product and analytics teams to integrate viewer data and improve content strategy Data Engineer, Analytic Partners 2023-2024

• Optimized SQL scripts with indexing, query structuring, cutting execution time from 3 hours to 45 minutes on 100M+ marketing records

• Led cross-functional meetings, analyzed campaign data with Snowflake and S3, used Adapta ETL to cut marketing budget spend 32%

• Used Apache Flink to enrich and transform marketing data in real-time, improving freshness and boosting campaign response by 25%

• Collaborated with stakeholders to migrate legacy marketing data to AWS, built Airflow DAGs for ETL process, saving 15 hours weekly

• Processed data files from raw PostgreSQL tables into AWS Redshift, improved data accessibility and saved 10 hours of processing time

• Developed REST APIs for customer data, helped marketing teams deliver personalized campaigns, increasing cross-sell revenue by 18% Data Engineer, Word Publishing 2019-2021

• Contributed to A/B tests using Optimizely and SQL, improving mobile app user retention by 15% through experimentation

• Generated Power BI, and Tableau data visualization utilizing plots, pie, bars saving 12 hours of manual work of each week

• Conducted exploratory data analysis (EDA) using Python and Pandas, leading to a 10% improvement in decision-making

• Designed Hadoop MapReduce jobs and optimized Hive queries, reducing data delays by 20% to support timely business decisions

• Designed scalable, high-performance SQL databases with HBASE, resulting in a 40% increase in data retrieval speed

• Analyzed pricing response data via Salesforce and Sheets, boosting customer acquisition by 10% through data-driven insights

• Managed millions of JSON records in Databricks using auto-scaling clusters, enhancing data load and Snowflake query speed by 40% Software Analyst, Value Score Business Solution 2018-2019

• Transitioned stakeholders to Tableau dashboards tracking 5+ KPIs, improving performance and saving nearly 10 hours weekly

• Implemented a new ERP system and trained and supported 20 finance professionals to ensure smooth adoption and data accuracy

• Migrated sales, CRM, supply chain, and financial data of enterprise applications on AWS, resulting in a 20% increase in productivity

• Developed 7+ MYSQL stored procedures, triggers integrated to pull large financial data; for SSRS reports increased reporting by 30% TECHNICAL SKILLS

• Language: Python(Numpy, Pandas, Scipy, Seaborn, Matplotlib, Scikit-learn), PySpark, R, Java

• Databases: MySql, PostgreSQL, T-SQL, SQL Server, MongoDB, Azure SQL

• Analytic Tool: Tableau, Power BI, Looker

• AWS Cloud: S3, EC2, Redshift, Lambda, RDS, Glue, VPC, Kinesis, DynamoDB

• Azure Cloud: Data Factory, Azure Synapse, Data Lake, Azure Databricks, Event Hub, Steam Job

• Big Data Tools: Hadoop, Hive, MapReduce, Kafka, Agile Scrum, Apache Spark, Kubernetes, Snowflake

• ETL & Tools: SSAS, SCDs, OLAP, OLTP, Talend, Git, SAS, CI/CD, Jira, Terraform, A/B tests, Informatica PROJECT

ETL Pipeline For Manufacturing Companies

• Designed a Talend ETL pipeline with Snowflake schema, integrating data into PostgreSQL and NoSQL for Tableau visualizations Olist E-Commerce Churn Risk Analysis

• Analyzed churn risk factors and delivery issues using Python; built Tableau dashboards to highlight key drivers and trends

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