Sai Krishna Modiboyena
Data Engineer | Databricks• Spark • Snowflake • AWS • SQL • Python | ETL • Data Pipelines • BI Dashboards
- Role
- Data Engineer at Aadyam Technologies
- Location
- Vermillion, SD, US
- LinkedIn followers
- 500 followers
About Sai Krishna Modiboyena
Data Engineer with 3+ years of experience designing real-time data pipelines, building scalable ETL workflows, and enabling analytics across cloud and on-prem environments. I specialize in streaming data, data warehousing, and creating end-to-end data solutions that drive business decisions.At Aadyam Technologies, I work on Apache Kafka and Spark Streaming to process high-volume clickstream and campaign data with sub-second latency. I build ETL/ELT pipelines on AWS and Snowflake, automate data quality checks, and develop dashboards in Power BI and Tableau to support marketing, product, and leadership teams.Previously, I worked as a Data Engineer Intern at Direct Companies and a Data Analyst at PwC, where I handled multi-source data, optimized SQL pipelines, performed DQA/DDA, and built dashboards for government and enterprise clients.I enjoy solving data problems through clean architecture, automation, and scalable systems.
Experience
Data Engineer
Apr 2025 — Present · Fairfield, NJ, US
Designed and deployed real-time data pipelines using Apache Kafka and Spark Streaming to process high-volume clickstreamand campaign data, enabling marketing teams to monitor user engagement with sub-second latency.• Built a scalable ETL framework to ingest, transform, and load data from AWS S3, MySQL, and REST APIs into aSnowflake data warehouse, supporting multi-source analytics and reporting.Developed Python-based data validation and anomaly detection scripts, improving data quality and reducing errors instreaming data by 30%.• Created interactive dashboards in Power BI and Tableau to visualize campaign performance, conversion metrics, andcustomer journey insights, cutting decision-making time by 35%.• Collaborated with marketing analysts and product managers to define KPIs, ensuring pipeline design and reporting alignedwith business objectives.• Optimized Spark Streaming jobs and Snowflake queries, reducing ETL runtime by 20% and improving overallsystem efficiency.
Education
Lovely Professional University
Bachelor of Technology - BTech, ECE
2017 — 2021
University of South Dakota
Master's degree, Computer Science
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