Naveen Kumar
@naveenkumar19
Big Data Engineer specializing in scalable PySpark pipelines and AWS data platforms.
What I'm looking for
I am a Big Data Engineer with over four years of hands-on experience designing, developing, and maintaining large-scale data systems and ETL pipelines. I specialize in building end-to-end PySpark solutions on AWS EMR, integrating data lakes (S3, HDFS) and optimizing Spark SQL for high performance.
I have designed and developed Spark applications using DataFrame transformations, Spark SQL and RDDs to implement complex aggregations, replication and synchronization jobs, and have experience handling semi-structured formats (Avro, Parquet, ORC) and schema compatibility in Hive.
I am adept at productionizing data workflows—configuring and managing EMR clusters, orchestrating pipelines with Airflow and Step Functions, debugging PySpark jobs, and collaborating with DevOps to ensure reliability and cost-effective resource utilization.
Experience
Work history, roles, and key accomplishments
Big Data Engineer
Tata consultancy services
Apr 2021 - Present (4 years 7 months)
Developed and optimized distributed Spark applications and PySpark pipelines on AWS EMR, integrated data lakes (S3/HDFS), and orchestrated workflows with Airflow to ensure high availability and improved job performance.
Worked on enterprise big data projects delivering Spark-based data processing, cluster optimization on AWS EMR, and end-to-end data pipeline development across large-scale datasets.
Education
Degrees, certifications, and relevant coursework
Mepco Schlenk Engineering College
Bachelor of Engineering, Engineering
Grade: 75%
Bachelor of Engineering with a reported score of 75%.
Sri Jayendra Swamigal Silver Jubilee Matriculation Higher Secondary School
Higher Secondary Certificate, Higher Secondary
Grade: 95%
Completed Higher Secondary (+2) with a reported score of 95%.
Rosemary Matriculation Higher Secondary School
Secondary School Certificate, Secondary Education
Grade: 97%
Completed 10th grade with a reported score of 97%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
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