SAI SANDILYA KOMMANA
Data Engineer
Bangalore, IN.About
Results-driven Data Engineer with 4+ years of experience in designing, building, and maintaining scalable big data pipelines. Proficient in Python, PySpark, Apache Airflow, and a suite of AWS services including S3, EMR, Lambda, CloudWatch, and CodeBuild. Adept at CI/CD automation, data modeling, and cloud-native engineering, consistently delivering optimized data solutions for analytics and reporting.
Work
Bangalore, Karnataka, India
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Summary
Currently serving as a Data Engineer at KPMG, designing and orchestrating scalable data pipelines and developing robust ETL workflows for critical data solutions.
Highlights
Designed and orchestrated scalable big data pipelines leveraging Apache Airflow and Apache Spark to process high-volume datasets.
Developed Python-based ETL workflows, integrating robust data quality validation to ensure data integrity and accuracy.
Automated deployments using AWS CodeBuild and managed infrastructure with Git-based CI/CD, streamlining release cycles.
Utilized AWS S3, EMR, Lambda, and CloudWatch to build and monitor scalable, cloud-native data solutions.
Optimized Directed Acyclic Graph (DAG) performance for time-sensitive batch data workflows, enhancing data delivery efficiency.
Mumbai, Maharashtra, India
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Summary
As a Data Engineer at NewAgelt Technologies, I built and maintained ETL pipelines, significantly improving data processing efficiency.
Highlights
Engineered and maintained ETL pipelines, improving overall data processing efficiency by 30% through strategic optimizations.
Integrated diverse data from heterogeneous sources into a centralized data warehouse, enabling unified analytics and reporting.
Tuned complex SQL queries and Spark jobs for optimized performance, reducing data retrieval and processing times.
Developed and maintained robust data models for various analytics and reporting use cases, supporting data-driven decision-making.
Provided proactive monitoring and rapid issue resolution for production workflows, minimizing downtime and ensuring data consistency.
Languages
English
Skills
Data Engineering
Big Data Pipelines, ETL, Data Modeling, Cloud-Native Engineering, Data Quality Validation, Data Delivery, Production Workflows, Data Warehousing, Data Integration, Data Optimization, Data Monitoring, Issue Resolution.
Programming Languages
Python, PySpark, SQL.
Cloud Platforms & Services
AWS S3, AWS EMR, AWS Lambda, AWS CloudWatch, AWS CodeBuild.
Big Data Technologies
Apache Airflow, Apache Spark.
DevOps & CI/CD
CI/CD Automation, Git.