Years of experience: 18

PythonSQLJavaSparkHiveHadoop

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Anurag's Career Path
Lead Software EngineerApr. 2019 -
Present
Persistent SystemsLead Software Engineer
• Understand business requirement and implement in PySpark/Spark SQL for executing on Palantir Foundry. • Participating in the design discussions and analyzing the problem in detail to understand the key points. • Coding & designing strategy. • Design of multiple modules for real time datasets. • Developing the schedule in Foundry to integrate all the PySpark/Spark SQL transformation code to...
Module Lead Software EngineerJun. 2015 -
Apr. 2022
Persistent SystemsModule Lead Software Engineer
Resoponsible for designing, developing, maintaining and deploying Big Data driven applications using Hadoop, MapReduce, Hive, Pig, Sqoop, Oozie, Storm, Flume, Spark, Kafka, Scalding, Cascading and HBase technologies. Responsible for 'Productionalizing' Hadoop applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning). Resoponsible for producing...
Module Lead Software EngineerJun. 2015 -
Apr. 2022
Persistent SystemsModule Lead Software Engineer
Resoponsible for designing, developing, maintaining and deploying Big Data driven applications using Hadoop, MapReduce, Hive, Pig, Sqoop, Oozie, Storm, Flume, Spark, Kafka, Scalding, Cascading and HBase technologies. Responsible for 'Productionalizing' Hadoop applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning). Resoponsible for producing...

Anurag's Posts

  • 0

    How I can help you

    I design and build end‑to‑end web and data systems using Java, Python, PySpark and modern big data stacks. I focus on robust object‑oriented design, cloud‑ready architectures, and reliable data flows that support analytics, reporting, and scalable products.

  • 0

    People I am looking for

    • Long‑term, data‑driven partnerships with product and tech teams • Companies needing cloud and big data platforms tuned for cost and speed • Teams at scale like Intuit, United Airlines, and similar data‑heavy businesses

  • 0

    Experience & Cases

    • 25% faster data processing via PySpark and Spark SQL tuning • 30% lower costs by moving on‑prem big data to AWS • Stable pipelines for structured and unstructured data • Scalable ingestion on Palantir Foundry • Served startups, solo founders, and larger enterprises

  • 0

    How to contact

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