🚀 Building scalable ETL pipelines | ☁️ Cloud Enthusiast | 📊 Data Lover
- 💼 Data Engineer with 4+ years of experience
- ☁️ Skilled in AWS, PySpark, SQL
- 🔄 Experienced in ETL pipelines
- 🌱 Currently learning Airflow & Kafka
- 🎯 Goal: To work in product-based companies
Hi, I’m Divyakeerthi Patnala from Vijayawada, Andhra Pradesh. I have around 4 years of experience working at Accenture, primarily in data engineering and ETL operations.
In my current role, I work on AWS-based data pipelines using services like Amazon S3, AWS Glue, Amazon EMR, and Amazon Athena. I’m involved in data ingestion, preprocessing, validation, and large-scale transformations using PySpark.
I handle both full load and incremental load processes, monitor production data pipelines, and perform reconciliation between systems to ensure data consistency. I also focus on handling data failures, performing root cause analysis, and improving pipeline performance.
Over time, I’ve developed a strong understanding of ETL workflows, and recently I’ve been focusing more on hands-on development in PySpark and optimization techniques.
I’m now looking for an opportunity where I can contribute more as a Data Engineer by building scalable and efficient data pipelines.
- Python
- PySpark
- SQL
- AWS
🚧 Coming Soon (Building real-world data engineering projects)
- 💼 LinkedIn: https://www.linkedin.com/in/divyakeerthipatnala
- 📧 Email: divyakeerthi403@gmail.com
⭐ Turning data into insights and scalable solutions