Open to opportunities

Aman Kumar Jha

@amankumarjha

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Data Engineer specializing in scalable ETL and cloud-native data platforms.

India

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What I'm looking for

I seek roles building scalable, reliable data platforms where I can optimize ETL pipelines, drive data quality, and collaborate cross-functionally to deliver production-ready data solutions.

I am a Data Engineer experienced in designing, developing, and deploying large-scale end-to-end ETL pipelines and cloud-native data solutions using PySpark, Snowflake, Kubernetes, and Airflow. I have optimized pipelines processing 1M+ daily records, reduced ETL runtime by 35%, and engineered Snowflake models that cut query latency by 25% while enabling sub-second analytics for business users.

I automate and orchestrate critical workflows (15+ automated with Astronomer Airflow), deploy containerized data applications on EKS with high uptime, and implement data quality, schema validation, and monitoring to ensure reliability. I collaborate with cross-functional teams to translate business needs into production-ready features and contribute to open-source Airflow and PySpark documentation.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Tata Consultancy Services

Aug 2024 - Present (1 year 10 months)

Designed and deployed PySpark ETL pipelines processing 1M+ daily records, reducing runtime by 35% and improving data processing efficiency by 30%; engineered Snowflake warehouse to cut query latency 25% and automated 15+ Airflow workflows to raise reliability to 99.5%.

Pyspark Snowflake Airflow Kubernetes AWS S3 ETL Data Modeling Performance Tuning

Education

Degrees, certifications, and relevant coursework

Vellore Institute of Technology

Bachelor of Technology, Computer Science and Engineering

2020 - 2024

Grade: 8.80/10

Activities and societies: Capstone project on computer vision (U-Net) for solar panel detection; coursework in Data Structures, DBMS, Cloud Computing, Machine Learning, Distributed Systems.

Bachelor of Technology in Computer Science and Engineering with a CGPA of 8.80/10; completed a capstone project developing a U-Net based model for solar panel detection achieving 92% IoU.