Rachit Mutreja, Developer in Kitchener, ON, Canada
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Rachit Mutreja

Verified Expert  in Engineering

Bio

Rachit is a senior back-end engineer with over a decade of experience building big data pipelines, microservices, and APIs. He is proficient in Java, Scala, and Python and is skilled in leveraging various AWS-managed and unmanaged services to build scalable and high-performance back-end systems. Rachit is excited to take on new challenges and new projects.

Portfolio

Nielsen
Java, Amazon Web Services (AWS), Spark, Microservices, RESTful Web Services...
Cognizant
Python 3, Hadoop, HDFS, Scrum, SQL, Yarn, PySpark, Agile
Optum
Scala, Unix, Unix Shell Scripting, Spark, Hadoop, HDFS, Yarn, Java...

Experience

Availability

Part-time

Preferred Environment

Linux, IntelliJ IDEA, GitHub, Slack, Spark, Java, Scala, Python 3

The most amazing...

...thing I've built is a re-usable all-in-1 scheduling system which took care of cluster management, and running Spark jobs on EMR.

Work Experience

Senior Software Developer

2021 - PRESENT
Nielsen
  • Developed a data pipeline that processes millions of data points near real-time using Spark on Amazon Elastic MapReduce (EMR).
  • Re-engineered an application build using microservices architecture to a modular monolith, reducing development, local testing, and deployment times.
  • Managed the CI/CD pipelines and overlooked the deployment process.
Technologies: Java, Amazon Web Services (AWS), Spark, Microservices, RESTful Web Services, Boto 3, Troposphere, Scala, Functional Programming, AWS Glue, Amazon Athena, Amazon EC2, AWS Lambda, Python 3, Amazon Elastic MapReduce (EMR), Amazon S3 (AWS S3)

Manager Projects

2020 - 2021
Cognizant
  • Designed and implemented Spark jobs to create an organized data layer on top of a data lake based on Apache Hive containing common variables to be used across the organization.
  • Created and delegated tasks to a team of four people based on their skill set, task priority, and risk.
  • Ensured any technical or operational blockers faced by the team were addressed.
Technologies: Python 3, Hadoop, HDFS, Scrum, SQL, Yarn, PySpark, Agile

Senior Software Engineer

2016 - 2020
Optum
  • Developed an on-premise data lake using the Hadoop ecosystem.
  • Built an ingestion system using Sqoop and Spark to ingest data from various sources into the data lake.
  • Automated the monitoring of the data ingestion process to reduce manual effort.
Technologies: Scala, Unix, Unix Shell Scripting, Spark, Hadoop, HDFS, Yarn, Java, Apache Airflow, Apache Sqoop

Senior Software Engineer

2015 - 2016
Impetus Technologies
  • Worked closely with a team of data scientists working on merchant transaction data for American Express to identify anomalies.
  • Developed an ETL process to push anomalous merchant data to Elasticsearch, which could be effectively indexed for better search capabilities like text search.
  • Designed and implemented REST APIs using the Spring MVC framework to retrieve data indexed in Elasticsearch.
Technologies: Hadoop, HDFS, Java, Elasticsearch, SQL, ETL, Spring, MapR, Apache Hive, Apache Pig, Unix Shell Scripting

Senior Software Engineer

2013 - 2015
Ness Digital Engineering
  • Developed a framework used by car dealers across the USA for building their websites and inventory management.
  • Ensured that the websites published by dealers were compliant with Web Content Accessibility Guidelines (WCAG).
  • Implemented a test-driven development (TDD) methodology within an Agile framework, utilizing the Rally Agile project management tool for efficient project planning and execution.
Technologies: Java, Spring, SQL, MySQL, Agile

Associate Consultant

2010 - 2013
Oracle
  • Customized and implemented FLEXCUBE, a core banking solution by Oracle, for over 10 clients.
  • Built complex PL/SQL procedures to migrate data from various legacy banking systems to a database schema defined for Oracle FLEXCUBE.
  • Generated insightful reports for clients using Oracle BI Publisher.
Technologies: Oracle, SQL, PL/SQL, Java, Oracle BI Publisher, Oracle WebLogic Application Server

Data Pipeline for Processing Near Real-time Ad Measurement Data

I was a back-end engineer who developed a data pipeline that collects and processes ad measurement data in near real-time. The pipeline would collect millions of data points using RESTful services, process them using Spark on Elastic MapReduce (Amazon EMR), and catalog them in AWS Glue for further analysis.

Libraries/APIs

PySpark

Tools

IntelliJ IDEA, Slack, Amazon Elastic MapReduce (EMR), GitHub, Boto 3, Amazon Athena, AWS CloudFormation, AWS Glue, GitLab CI/CD, Apache Airflow, Apache Sqoop, Oracle BI Publisher

Languages

Scala, Java, Python 3, SQL

Frameworks

Spark, Hadoop, Yarn, Spring

Platforms

Amazon Web Services (AWS), AWS Lambda, Amazon EC2, Linux, Unix, MapR, Apache Pig, Oracle

Paradigms

Microservices, Functional Programming, Scrum, Agile, ETL

Storage

Amazon DynamoDB, Amazon S3 (AWS S3), HDFS, Elasticsearch, Apache Hive, MySQL, PL/SQL

Other

Troposphere, SA, RESTful Web Services, Unix Shell Scripting, Oracle WebLogic Application Server

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