Yuvraj  ·  ML Engineer  ·  5+ yrs

Mid-Level
India5+ years experienceremote
Available within 48 hrs

About Yuvraj

Yuvraj is a skilled Data ML OPS Engineer with extensive experience in big data processing and analytics. He has successfully transitioned into MLOps, leveraging his strong background in AWS and Databricks to enhance machine learning workflows. His expertise includes designing real-time data pipelines, performing cloud migrations, and implementing data quality measures. Yuvraj is adept at utilizing tools like Apache Airflow for orchestration and has a solid understanding of DevOps practices.

Core expertise

AWS
cloud
10/10
Apache Spark
language
10/10
Python
language
10/10
Databricks
tooling
10/10
AA
Apache Airflow
devops
8/10
Salesforce
cloud
8/10

Additional skills(20)

DatabricksPythonPySparkSQL ServerMySQLPostgreSQLAWS S3AWS GlueAWS KinesisCloudwatch

Why hire Yuvraj?

Production deploy authorityDesigned real-time data pipelinesOptimized machine learning workflows

Designed and implemented multiple real-time financial data pipelines on AWS

Developed automated PySpark workflows for large-scale data processing

Successfully transitioned data processing strategies to AWS Glue jobs

Developed automated PySpark workflows for analyzing large-scale credit card transaction data

Successfully transitioned data processing strategies from SQL queries to AWS Glue jobs, significantly improving ETL processes

Project highlights(5)

Real-Time Financial Data Pipeline – Data ML OPS Engineer

Overview: This project designed and implemented a real-time financial data pipeline using the Finnhub API. Responsibilities: Designed and implemented a comprehensive real-time financial data pipeline on AWS. Utilized Databricks for scalable data ingestion and processing, supporting fintech applications like algorithmic trading.

DatabricksPythonPySparkAWS S3AWS GlueAWS KinesisCloudwatch

Key outcomes:

  • Successfully designed and implemented a real-time financial data pipeline on AWS

  • Created a scalable data engineering solution for real-time financial market data

Cloud Data Migration – Data ML OPS Engineer

Overview: This project focused on transitioning an organization's data from on-premises systems to cloud-based platforms. Responsibilities: Developed automated PySpark workflows for analyzing large-scale credit card transaction data on AWS S3. Optimized data storage and processing strategies to leverage cloud-based analytics.

PySparkAWS S3Shell ScriptingAWS LambdaSQL ServerCloudwatchApache Airflow

Key outcomes:

  • Successfully migrated an organization's data from on-premises to cloud platforms

  • Developed automated PySpark workflows for large-scale credit card transaction data

Credit Card Data Analysis – Data ML OPS Engineer

Overview: This project involved extracting, processing, and analyzing credit card transaction data using PySpark. Responsibilities: Created comprehensive data pipelines for banking operations. Used Databricks on AWS to process and transform data from multiple sources.

PySparkShell ScriptingAWS S3Databricks

Key outcomes:

  • Created comprehensive data pipelines specifically for banking operations

  • Developed PySpark programs to efficiently extract and analyze delta data from S3

RM Workbench Project – Data ML OPS Engineer

Overview: This project developed a comprehensive set of data pipelines for various aspects of banking operations, including employee incentives and performance ranking. Responsibilities: Implemented data pipelines using PySpark, Airflow, and Nutanix Object-store as the Datalake.

PySparkNutanix Object-storeApache AirflowAWS EMRAWS S3AWS GlueAWS RedshiftShell ScriptingCronjobsPythonMySQLPostgreSQL

Key outcomes:

  • Implemented data pipelines for calculating customer delinquency rates for credit cards and loans

  • Successfully processed and consolidated data from multiple sources for banking operations

Data Transformation Strategy Enhancement – Data ML OPS Engineer

Overview: This project involved enhancing data transformation strategies by transitioning from traditional SQL queries to AWS Glue jobs. Responsibilities: Successfully transitioned data processing from SQL queries on Redshift to AWS Glue jobs.

AWS GlueAWS RedshiftPythonSQLPySparkAWS Lambdaboto3AWS SNS

Key outcomes:

  • Successfully transitioned data processing strategy from SQL queries to AWS Glue jobs, resulting in improved ETL

  • Enhanced data processing efficiency through the development of PySpark jobs for transformation and aggregation

5+ years of industry experience

FinTech4 projects
  • •Real-Time Financial Data Pipeline— Data ML OPS EngineerDatabricks · Python · PySpark · AWS S3 +3
  • •Cloud Data Migration— Data ML OPS EngineerPySpark · AWS S3 · Shell Scripting · AWS Lambda +3
  • •Credit Card Data Analysis— Data ML OPS EngineerPySpark · Shell Scripting · AWS S3 · Databricks
  • •RM Workbench Project— Data ML OPS EngineerPySpark · Nutanix Object-store · Apache Airflow · AWS EMR +8
InsuranceReported in resume
Banking2 projects
  • •Credit Card Data Analysis— Data ML OPS EngineerPySpark · Shell Scripting · AWS S3 · Databricks
  • •RM Workbench Project— Data ML OPS EngineerPySpark · Nutanix Object-store · Apache Airflow · AWS EMR +8
Logistics & Supply ChainReported in resume

Ready to work with Yuvraj?

Onboard within 48 hours. No long hiring cycles, no recruiter middleman.

At a Glance

LocationIndia
Experience5+ years
Work moderemote
Direct hirePossible
Start within48 hours
From$2,299/ month

Single contract. Billed in USD.

Typically responds within 4 business hours.

5-day replacement guarantee
48-hour onboarding, single invoice
Direct chat — no recruiter middleman

Top Skills

AWS
10/10
Apache Spark
10/10
Python
10/10
Databricks
10/10
Apache Airflow
8/10
Seniority signals
Owns production deploysGreenfield architectSystem owner
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Background & identity checked
English communication verified
Ready to onboard in 48 hours

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Yuvraj

MLOps