Hi, I’m Paavana Raghunandan Vallabhaneni, a data engineer and analyst with hands-on experience designing and optimizing large-scale batch and streaming pipelines across enterprise, IoT, and education analytics domains. I build cloud-native data solutions using Apache Spark, Databricks, Kafka, and Airflow across AWS, Azure, and Snowflake. I’m passionate about turning data into actionable insights and reliable data platforms that scale with business needs. I’m proficient in automated ETL frameworks, real-time data workflows, and reliability enhancements with Python, SQL, dbt, and Informatica. I’ve delivered end-to-end solutions that cut processing time by 20 hours weekly and sped up releases by 3 days, enabling faster decision-making for product and operations teams.

Paavana Raghunandan Vallabhaneni

Hi, I’m Paavana Raghunandan Vallabhaneni, a data engineer and analyst with hands-on experience designing and optimizing large-scale batch and streaming pipelines across enterprise, IoT, and education analytics domains. I build cloud-native data solutions using Apache Spark, Databricks, Kafka, and Airflow across AWS, Azure, and Snowflake. I’m passionate about turning data into actionable insights and reliable data platforms that scale with business needs. I’m proficient in automated ETL frameworks, real-time data workflows, and reliability enhancements with Python, SQL, dbt, and Informatica. I’ve delivered end-to-end solutions that cut processing time by 20 hours weekly and sped up releases by 3 days, enabling faster decision-making for product and operations teams.

Available to hire

Hi, I’m Paavana Raghunandan Vallabhaneni, a data engineer and analyst with hands-on experience designing and optimizing large-scale batch and streaming pipelines across enterprise, IoT, and education analytics domains. I build cloud-native data solutions using Apache Spark, Databricks, Kafka, and Airflow across AWS, Azure, and Snowflake. I’m passionate about turning data into actionable insights and reliable data platforms that scale with business needs.

I’m proficient in automated ETL frameworks, real-time data workflows, and reliability enhancements with Python, SQL, dbt, and Informatica. I’ve delivered end-to-end solutions that cut processing time by 20 hours weekly and sped up releases by 3 days, enabling faster decision-making for product and operations teams.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Language

English
Fluent

Work Experience

Data Engineer at Uber
March 1, 2025 - Present
Engineered scalable batch and streaming data pipelines using Apache Spark and Kafka on Databricks, enabling ingestion of 120M+ records/month across IoT and ERP sources, enhancing reporting timeliness for product teams by 6 hours. Deployed ETL workflows with Airflow, Informatica, and dbt, integrating with AWS Glue, S3, and RDS, reducing manual data processing time by 18 hours/week. Containerized ETL components with Docker and managed deployments via GitHub Actions and Terraform, accelerating feature rollout cycles by 3 days/month. Implemented data validation and unit testing across 200+ tables to improve schema consistency and reduce post-deployment rollbacks.
Research Analyst at Auburn University
June 1, 2023 - October 1, 2024
Extracted and ingested millions of structured data rows into Snowflake via automated pipelines, enabling scalable storage for institutional reporting. Developed AWS Lambda functions in Python for real-time and batch transformations, streamlining data cleansing and enrichment for quarterly performance reports. Processed over 1 million classroom performance records quarterly with optimized ETL to meet stringent audit standards. Created interactive Power BI dashboards to visualize insights for educational resource planning.
Data Engineer at Dell Technologies
April 1, 2020 - July 1, 2022
Built cloud-native ETL pipelines using Apache Spark, Informatica, and AWS Glue to process over 200 million telemetry events daily from Dell storage devices, accelerating diagnostics reporting by 5 hours. Streamlined real-time transformations with Kafka, dbt, and Delta Lake on Azure Synapse, improving hardware visibility and reducing incident triage time. Implemented 150 validation checks across 120+ production tables to safeguard data integrity. Migrated 15 legacy data marts to Snowflake, improving query runtimes. Coordinated with DevOps and compliance teams to provision secure infrastructure with Terraform and IAM, and established logging/health monitoring via Jenkins and CloudWatch.

Education

Master's in Data Science and Engineering at Auburn University
August 1, 2023 - December 1, 2024
Master's in Data Science and Engineering at Auburn University
August 1, 2023 - December 1, 2024

Qualifications

AWS Certified Cloud Practitioner
January 11, 2030 - January 29, 2026
Databricks Certified Data Engineer Associate
January 11, 2030 - January 29, 2026
Snowflake: SnowPro CORE Certification
January 11, 2030 - January 29, 2026
AWS Certified Cloud Practitioner
January 11, 2030 - January 29, 2026
Databricks Certified Data Engineer Associate
January 11, 2030 - January 29, 2026
Snowflake SnowPro CORE Certification
January 11, 2030 - January 29, 2026

Industry Experience

Education, Software & Internet, Manufacturing, Professional Services, Other, Transportation & Logistics, Media & Entertainment