Tejaswi Vadapalli
Data Engineer
Building efficient data pipelines and real-time processing solutions with AWS, GCP, and Salesforce.
About Me
Tejaswi Vadapalli
Data Engineer with 2+ years of experience in AWS, GCP, and Salesforce, specializing in Python, SQL, and Java to build efficient ETL pipelines and real-time data processing solutions. Proficient in Apache Kafka and Airflow to streamline workflows and enhance data accessibility.
Currently pursuing M.S. in Information Systems at Northeastern University, Boston. Passionate about transforming complex data into actionable insights and building scalable data solutions.
Python90%
SQL85%
AWS80%
GCP75%
Salesforce70%
Apache Spark75%
Apache Airflow80%
Data Modeling85%
Projects
Predictive Model for Taxi Trip Duration
Developed an interactive dashboard using Tableau and Dash to visualize real-time travel data, serving over 500 daily users. Engineered a predictive model using Python with Scikit-learn and XGBoost on 10M+ taxi trip records.
Python
Tableau
Dash
Scikit-learn
XGBoost
AWS Lambda
S3
Linear Regression Analysis of Lending Club Loan Data
Performed linear regression analysis on 2.25M+ Lending Club loan records using Python to identify critical predictors of repayment amounts. Designed and optimized data processing pipelines using Python and PostgreSQL.
Python
Pandas
NumPy
PostgreSQL
Linear Regression
Work Experience
Data Engineer at Saayam For All
Feb 2025 – Present San Jose, USA
- Designed and optimized Tableau dashboards to monitor ETL performance, reducing error rates by 30% and improving data integrity for enhanced reporting accuracy.
- Led in-depth SQL analysis of user engagement trends, driving a 15% increase in targeted recommendations and improving personalization strategies.
- Developed and enforced data validation processes using Apache Airflow, minimizing inconsistencies by 35% and ensuring high-quality data across operational pipelines.
- Automated data transformation workflows with Pandas and PySpark, decreasing manual intervention by 40% and boosting data processing efficiency.
Data Engineer Intern at Nebula Partners LLC
Jan 2024 – Aug 2024 Alpharetta, USA
- Engineered and optimized ETL pipelines using Python and SQL, accelerating data processing by 25% and enhancing machine learning model performance, which improved user engagement by 15%.
- Designed and normalized a MySQL database to 3NF, integrating Python-based automation for data ingestion and cleaning, streamlining trend analysis for business decision-making.
- Led a cross-functional migration of databases to AWS RDS, cutting infrastructure costs by 30% while enhancing scalability and accessibility for analytics teams.
- Integrated Apache Airflow for automated data quality checks, reducing inconsistencies by 40% and ensuring high-fidelity data for business intelligence reporting.
Data Engineering Analyst at Accenture
Jul 2021 – Oct 2022 Hyderabad, India
- Designed and optimized data models in PostgreSQL and MongoDB, aligning storage structures with business logic to improve query performance by 30% and reduce response times.
- Architected multi-cloud data pipelines across AWS, GCP, and Salesforce, synchronizing disparate data sources to improve system interoperability and increase data availability by 20%.
- Developed automation scripts using Python and KornShell scripting, reducing manual interventions and improving operational efficiency by 40% in ETL workflows.
- Built scalable, production-ready ETL pipelines using BigQuery and Git, enabling real-time data ingestion that powered critical business insights for enterprise clients.