Sai Rohith Tulasi

Data Engineer @Clairvoyant

TX, US

Spearheaded migration of legacy batch pipelines using HDFS and MapReduce to near real-time data processing with AWS Glue ETL, S3, and Redshift, reducing data latency by 70% and enabling faster analytics for 10+ business teams.• Designed and maintained scalable cloud-native ETL/ELT pipelines using Databricks, Spark, Python, SQL, and Azure Data Factory, processing 5TB+ daily with 99.9% reliability and 35% faster ingestion.• Improved data quality by implementing automated validation and cleansing with PySpark, Python, and MongoDB, reducing downstream errors by 50% and mitigating risks related to AI hallucination and manual mistakes.• Architected and optimized data models and warehouses on Snowflake, Azure Data Lake, Redshift, and Oracle, boosting query performance by 40%, ensuring accuracy and compliance, and cutting costs by 30%.• Automated infrastructure provisioning with Terraform and CI/CD pipelines using Git and Jenkins, reducing deployment times by 40%, increasing deployment efficiency, and lowering pipeline failures by 20%.• Proactively troubleshot and optimized complex SQL queries and Spark jobs using T-SQL, Scala, and TensorFlow, improving system reliability and reducing processing times by 15%.• Built scalable machine learning feature pipelines leveraging Databricks, Azure ML, and MLflow, improving feature availability and model retraining efficiency by 30%, supporting faster and more accurate AI-driven business insights.• Collaborated with data scientists and stakeholders to deploy reusable feature stores in Databricks, orchestrate Airflow workflows, and deliver clean Tableau data models, accelerating model training by 30%.

Resonance Junior college

Intermediate, MPC

Holy Angels High School

SSC, High School

The University of Texas at Arlington

Master's degree, Computer Science

Kakatiya University, Warangal

Bachelor of Technology, Computer Science