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Vetted Talent

Monica Kherajani

Vetted Talent
Disciplined and insightful data engineer with 5.5 years of experience in building real time data pipelines, ETL pipelines, implementing security aspects, creating visualizations and providing useful business insights.
  • Role

    Lead Data Engineer

  • Years of Experience

    6 years

Skillsets

  • Restful APIs - 3 Years
  • ETL - 5 Years
  • REST - 3 Years
  • Airflow - 1 Years
  • AWS Lambda
  • Scrum
  • Data Engineer - 5 Years
  • Big Data - 5 Years
  • MySQL - 5 Years
  • Data Pipelines - 5 Years
  • Git - 2 Years
  • Spark - 3 Years
  • pandas - 5 Years
  • Data Pipeline - 5 Years
  • Data Migration - 3 Years
  • PowerBI - 2 Years
  • REST API - 3 Years
  • AWS
  • CI/CD
  • Data Analysis
  • EMR
  • Logstash
  • NO SQL
  • PowerBI
  • Step functions
  • Agile
  • Python - 5 Years
  • Elasticsearch
  • Elasticsearch - 4 Years
  • PySpark - 4 Years
  • SQL
  • SQL - 4 Years
  • AWS - 3 Years
  • Relational DB - 1 Years
  • Data Analysis - 05 Years
  • Redshift - 5 Years
  • Shell Scripting - 4 Years
  • Python
  • Github
  • Lambda
  • NO SQL - 4 Years
  • Jira
  • CI/CD - 2 Years
  • Kafka - 2 Years
  • Unix/Linux
  • Kibana
  • S3 - 3 Years
  • Glue
  • Logstash

Vetted For

13Skills
  • Roles & Skills
  • Results
  • Details
  • icon-skill_image
    Data Engineer || (Remote)AI Screening
  • 72%
    icon-arrow-down
  • Skills assessed :Airflow, Data Governance, machine learning and data science, BigQuery, ETL processes, Hive, Relational DB, Snowflake, Hadoop, Java, Postgre SQL, Python, SQL
  • Score: 65/90

Professional Summary

6Years
  • Mar, 2022 - Present3 yr 4 months

    Senior Data Engineer

    Kyndryl
  • Sep, 2019 - Feb, 20222 yr 5 months

    Data Engineer

    Larsen Toubro Infotech

Applications & Tools Known

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    Python

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    Elasticsearch

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    Kibana

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    AWS

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    S3

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    Glue

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    Redshift

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    AWS Lambda

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    Jira

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    Power BI

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    Kafka

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    Cassandra

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    Logstash

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    Spark

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    Kibana

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    Github

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    Agile

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    Shell scripting

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    CI/CD

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    SQL

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    NOSQL

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    Unix/Linux

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    Kafka

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    GitHub

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    Agile

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    Scrum

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    Airflow

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    CI/CD

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    Kibana

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    AWS

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    SQL

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    Data Analysis

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    Agile

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    Shell Scripting

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    CI/CD

Work History

6Years

Senior Data Engineer

Kyndryl
Mar, 2022 - Present3 yr 4 months
    Developed ETL data processing pipeline using Python, Elasticsearch, Kibana Reading multiple csv files, performing transformations on them using NumPy, Pandas and delivering useful business insights. Engineered and deployed an ETL pipeline in AWS using AWS Glue, S3, Redshift, and Power BI, extracting data from Jira API and Project Rak API to analyze teams, boards, and sprints, optimizing resource allocation for 30% efficiency boost. Integrated data from APIs to build analytical dashboards. Automated Backup reporting thus reducing manual efforts by 40%. Implemented best practices for clear logging mechanism. Effectively communicated client needs, guiding team members towards meeting project requirements. Working on POC using Data Migration service in AWS to migrate data from oracle to redshift. Established POC to read data from Kafka topics in spark using PySpark.

Data Engineer

Larsen Toubro Infotech
Sep, 2019 - Feb, 20222 yr 5 months
    Achieved Realtime data reconciliation using Kafka, Cassandra, Logstash, Elasticsearch, Kibana. Upgraded Elasticsearch, Logstash, Kibana, File beat to latest version. Implemented Authentication, Authorization, SSL in ELK stack. Automated deployment of config files using shell script. Designed dashboards in Kibana for monitoring logs using File beats. Automated committing of git artifacts thus saving developers time by 20%. Built real time data pipeline to automate data collection from Kafka. Increased performance of system by 30% based on parameters JVM heap size, worker, threads.

Achievements

  • Developed ETL data processing pipeline using Python, Elasticsearch, Kibana
  • Engineered and deployed an ETL pipeline in AWS
  • Automated Backup reporting thus reducing manual efforts by 40%
  • Implemented best practices for clear logging mechanism
  • Established POC to read data from Kafka topics in Spark using Spark
  • Achieved Realtime data reconciliation using Kafka, Cassandra, Logstash, Elasticsearch, Kibana
  • Upgraded Elasticsearch, Logstash, Kibana, File beat to latest version
  • Implemented Authentication, Authorization, SSL in ELK stack
  • Automated deployment of config files using shell script
  • Designed dashboards in Kibana for monitoring logs using File beats
  • Automated committing of git artifacts thus saving developers time by 20%
  • Built real time data pipeline to automate data collection from Kafka
  • Increased performance of system by 30% based on parameters JVM heap size, worker, threads
  • Appreciated by clients for exceeding the clients requirements.
  • Automated Backup reporting thus reducing manual efforts by 40%.
  • Optimized resource allocation for 30% efficiency boost.
  • Automated committing of git artifacts thus saving developers time by 20%.
  • Increased performance of system by 30% based on parameters JVM heap size, worker, threads.
  • Engineered and deployed an ETL pipeline in AWS using AWS Glue, S3, Redshift, and Power BI, optimizing resource allocation for 30% efficiency boost.
  • Implemented best practices for clear logging mechanism.
  • Developed ETL data processing pipeline using Python, Elasticsearch, Kibana. Reading multiple CSV files, performing transformations on them using NumPy, Pandas and delivering useful business insights.
  • Engineered and deployed an ETL pipeline in AWS using AWS Glue, S3, Redshift, and Power BI, extracting data from Jira API to analyze teams, boards, and sprints, optimizing resource allocation for a 30% efficiency boost.
  • Integrated data from APIs to build analytical dashboards.
  • Effectively communicated client needs, guiding team members towards meeting project requirements.
  • Working on POC using Data Migration service in AWS to migrate data from Oracle to Redshift.
  • Established POC to read data from Kafka topics in spark using Spark.
  • Achieved Realtime data reconciliation using Kafka, Cassandra, Logstash, Elasticsearch, Kibana.
  • Upgraded Elasticsearch, Logstash, Kibana, Filebeat to latest version.
  • Implemented Authentication, Authorization, SSL in ELK stack.
  • Automated deployment of config files using shell script.
  • Designed dashboards in Kibana for monitoring logs using Filebeats.
  • Built real-time data pipeline to automate data collection from Kafka.

Major Projects

1Projects

Education

  • Bachelor of Engineering

    Walchand Institute of Technology (2019)

Certifications

  • Nptel oops

  • Ibm cognitive class: big data 101

  • Nptel cloud computing

  • Nptel joy of computing using python