Sujith K. Email & Phone Number

Fairfax, Va, Us

Westlake, Texas, Us

Designed and developed a security framework using AWS Lambda and DynamoDB to provide fine-grained accesscontrol to objects in AWS S3.Developed AWSLambda functions with Boto3 to automate the deregistration of unused Amazon Machine Images(AMIs) in all application regions, reducing EC2 resource costs. Conducted end-to-end architecture and implementation assessments of AWS services such as Amazon EMR,Redshift, and S3. Implemented machine learning algorithms using Python to perform predictions by leveraging Kinesis Firehose and S3 data lake.Utilized AWS EMR to efficiently transform and move large volumes of data between different AWS data stores anddatabases, such as Amazon S3 and Amazon DynamoDB.Implemented AWS Step Functions to automate and orchestrate tasks related to Amazon Sage Maker, such as datapublishing to S3, model training, and deployment for prediction.Integrated Apache Airflow with AWS to monitor multi-stage machine learning workflows with tasks running onAmazon Sage Maker.Environment: AWS, HDFS, Map Reduce, Kinesis, Airflow, Unix, Tableau, Kafka, Docker, Spark, Hive, Oracle, Db2, Pyspark,SQL, Kubernetes, Kibana, Python, Django, SQL Alchemy, Spyder, PyCharm, Sublime Text.

Orlando, Fl, Us

Worked with AWS Glue to process and integrate data from various sources into Amazon Redshift.Developed data pipelines using AWS Data Pipeline to move and transform data between different AWS services.Created Python scripts for automating tasks, data processing, and analysis.Designed and built web applications using Python, Django, and Flask, incorporating CSS, HTML, and XML forfrontend development. Developed SOAP-based Web Services for sending and receiving data. Implemented RESTful APIs using Node.js and Sequelize.js for database operations Utilized Python libraries like Pandas and NumPy for data manipulation and analysis. Created data visualizations using libraries like Matplotlib and Seaborn. Developed dashboards and reports using tools like SQL Server Reporting Services (SSRS) and Power BI. Worked with Terraform for managing infrastructure and provisioning resources in AWS. Employed Apache Spark for data processing and analysis, enhancing data-driven decision-making. Utilized Amazon EMR clusters for distributed data processing, significantly improving data insights. Designed and maintained ETL pipelines to prepare and transform data for analysis. Successfully transitioned from a Python Developer role to a Data Engineer, gaining proficiency in big datatechnologies.AWS Glue, AWS Data Pipeline, Amazon Redshift, Amazon Web Services (AWS), Terraform, Python, Java,JavaScript, Django, Flask, CSS, HTML, XML, SOAP-based Web Services, RESTful APIs, Sequelize.js, Pandas, NumPy,Matplotlib, Seaborn, SQL Server Reporting Services (SSRS), Power BI, Docker, PostgreSQL, GitHub, AWS Cloud PlatformDesign, CI/CD Pipelines, Dynamic Scalability, High Availability, Fault Tolerance, Reliable Application Deployment, ExpertKnowledge in AWS Best Practices, Security, Governance, and Compliance in AWS.

Minneapolis, Mn, Us

Possess hands-on experience in Amazon Web Services (AWS) and its services, including Amazon Redshift, Amazon S3(Simple Storage Service), AWS Lambda, AWS Glue, Amazon Data Pipeline, Amazon EMR, and Amazon CloudWatch.Utilized AWS CloudShell to configure services such as Amazon EMR, Amazon S3, and Amazon Redshift in AWS.Developed Power BI reports leveraging Azure Analysis Services to optimize performance and enhance data analysis capabilities using Amazon Redshift.Utilized PyUnit as the unit test framework for all Python applications and accessed database objects using Django Database APIs. Orchestrated data pipelines with AWS Step Functions, simplifying data transformation and delivery. Implemented load balancing and auto-scaling configurations using AWS ECS, guaranteeing application reliability. Utilized Amazon EMR for machine learning and advanced analytics on large datasets. Designed serverless applications on AWS, reducing infrastructure management overhead.Demonstrated proficiency in AWS IAM (Identity and Access Management) for secure resource access.Continuously improved cost management and optimization of AWS services through monitoring and analysis.

Naperville, Illinois, Us

Utilized Python libraries for tasks such as web scraping with Beautiful Soup, performing complex calculations using NumPy, SciPy, Matplotlib, and Pandas, and creating graphical user interfaces (GUIs) with Tkinter.Wrote Python scripts by utilizing Pandas, to parse and load data from JSON files into databases. Implemented programs using NumPy and SQL Alchemy to calculate performance metrics. Created a template webpage that displays REST API's get and post methods based on user search criteria.Built web applications following the Model-View-Controller (MVC) architecture and utilized RESTful and SOAP web services.Developed data-driven applications using Python 2.7 and Python 3.0, primarily using PyCharm and Anaconda Spyder IDEs.Used Python and Django to interface with the jQuery UI and manage the storage and deletion of content.Developed CRUD applications using the MERN stack (MongoDB, Express, ReactJS, and NodeJS) and REST-based APIs.Conducted data analysis and profiling to identify key join relationships, assess data types, and evaluate data quality using SQL queries.Implemented a Lambda function to trigger the AWS Glue job based on the defined S3 event.Configured monitors, alarms, notifications, and logs for Lambda functions and Glue Jobs using CloudWatch.Utilized AWS Glue catalog with crawler to extract data from S3 and performed SQL query operations using AWS Athena.Created external tables with partitions using AWS Athena and Redshift for optimized data storage and retrieval.Designed and developed ETL processes using AWS Glue to migrate Campaign data from external sources like S3, Parquet/Text Files into AWS Redshift.Worked with Spark ecosystem using Scala and HIVE Queries on different data formats like Text file and parquet.Utilized Spark API over Cloudera and Hortonworks Hadoop YARN for performing data analytics on Hive.

Designed and transformed layers to write the ETL using Scala and Spark and distributed them among the team.Designed and developed Spark jobs with Scala to implement an end-to-end data pipeline for batch processing.Worked with automation tools like Jenkins, Artifactory, SonarQube Chef, and Puppet for continuous integration and continuous delivery (CI/CD) for implementing end-to-end automation tasks.Utilized Rest API with python for ingesting data into BigQuery.Developed web-based applications using Python, Django, Flask, PHP, C++, XML, HTML, JavaScript and developed consumer-based features using Test driven Development (TDD).Developed a module for building Django ORM Queries which is useful for pre-loading the data.Monitored BigQuery, Dataproc, and Cloud Dataflow jobs via Stackdriver for all environments.Utilized G-cloud function with Python to load data into BigQuery for on-arrival CSV files in GCS bucket and analyzed various types of raw files like JSON, CSV,XML with Python using Pandas, Numpy, etc.Processed and loaded bound and unbound data from Google Pub/Subtopic to BigQuery using Cloud Dataflow with Python.Utilized Python library Matplotlib for creating charts, graphs and Pickle, Python-twitter, Pandas, Urllib2,BeautifulSoup for database connectivity and used NLTK for processing text data.Deployed the project into Heroku and Worked with version control tools such as GitHub, and AWS code commit.