P Sai Likhitha

Data Engineer with 2+ years of overall experience, building scalable ETL/ELT pipelines and migrating large-scale workloads from Hadoop to the cloud. Strong expertise in PySpark, Databricks, SQL, and Python, with experience on Azure and AWS, cutting pipeline runtime by about 40% and implementing data quality validation checks across ETL stages. Brings a hands-on, quality-focused approach to delivering reliable data for analytics, backed by CI/CD automation experience and published research on RAG systems.

Cloud Automation Intern at Signify Innovation Labs (2025-07 – 2026-05)

• Refactored 8 existing CI/CD pipelines by migrating shell-script logic to reusable Jenkins Shared Libraries.
• Built a secure file upload and download workflow for an SLM portal using AWS Lambda, Amazon S3, and DynamoDB, using pre-signed S3 URLs to overcome Lambda payload limitations.
• Built a Jenkins Shared Library function that hashes the Dockerfile (SHA-256) and checks Amazon ECR: on a match it pulls the existing image, otherwise it builds and pushes, cutting the tested build times from about 20 to 5 minutes.

Programmer Analyst (Data Engineer) at Cognizant Technology Solutions (2023-02 – 2024-06)

Project: Data Migration from Hadoop to Cloud (Databricks)

• Migrated Spark ETL jobs from Hadoop HDFS to the cloud using a medallion architecture, ingesting PostgreSQL data into ADLS Gen2 (Bronze) with Azure Data Factory, transforming it in Databricks with PySpark into Delta Lake (Silver), and loading it into Snowflake using the Spark Snowflake connector for analytics and reporting.
• Scheduled and orchestrated the end-to-end PySpark workflows, from ingestion through the Snowflake load, with ADF pipelines.
• Applied Spark performance tuning (broadcast joins, salting, caching, persistence), including broadcast joins to merge large financial transaction tables with smaller reference datasets, reducing shuffle operations and cutting job runtime from 4 hours to 2.4 hours (about 40%).
• Implemented data quality validation checks in PySpark (null checks, duplicate detection, schema validation, and source-to-target row-count reconciliation) to ensure accurate migration from legacy databases to Snowflake.
• Project: Business Intelligence & Dashboard Development (Qlik Sense)
• Developed and maintained interactive Qlik Sense dashboards using set analysis to enable data-driven business decision-making.
• Worked in an Agile/Scrum team (stand-ups, sprints); gathered requirements and contributed to Business Requirement Documents (BRDs).

Data Engineering Intern at Cognizant Technology Solutions (2022-02 – 2022-08)

• Trained in SQL, Azure, Databricks, and Power BI, building a foundation in cloud data engineering and analytics.
• Developed Power BI dashboards for the final project, turning project data into visual reports for analysis.

M.Tech in Computer Science and Engineering – Vellore Institute of Technology (VIT) (2024-07 – 2026-08)

B.E. in Electronics and Communication Engineering – SRM Easwari Engineering College (2018-08 – 2022-04)