Kranthi Kumar Email & Phone Number

Texas, United States

Columbia, South Carolina, Us

Participated in Agile delivery, SAFe, and DevOps frameworks, and use DevOps tools for planning, building, testing, releasing, and monitoring Develop, implement, and maintain CI/CD pipelines for Big Data solutions using Azure DevOps. Work closely with development teams to ensure that code is deployed successfully to the production environment.Created reusable YAML pipelines for data processing and data storage using Azure Data Factory, Data Lake, and Databricks. Used Git flow branching strategy to manage code changes and code deployments.Worked with PowerShell scripting, Bash, YAML, Json, GIT, Rest API, and Azure Resource Management (ARM) templates to build and manage CI/CD pipelines.Implemented standards and best practices for the CI/CD framework, including version control, code review, and testing.Used security scanning/monitoring tools to ensure that code is free from vulnerabilities and integrated those tools with the CI/CD pipeline.Collaborated with development teams to troubleshoot issues and debug code on Windows environments. Provided guidance to junior engineers on best practices for CI/CD pipelines and cloud-native architectures.Developed solutions in Databricks for Data Extraction, transformation, and aggregation from multiple data sources. Designed and implemented highly performant data ingestion pipelines from multiple sources using Azure Data Factory and Azure Databricks. Built SCD Type 2 Dimensions and Facts using Delta Lake and Databricks. Developed custom-built ETL solution, batch processing, and real-time data ingestion pipeline to move data in and out of the Hadoop cluster using PySpark and Shell Scripting.

Developed and implemented CI/CD pipelines for Big Data solutions on Azure Cloud platform. Worked closely with development teams to ensure successful deployment of code to the production environment.Created continuous integration and delivery pipelines using Azure Data Factory, Data Lake, and Databricks. Managed code changes and code deployments using Git flow branching strategy.Used PowerShell scripting, Bash, YAML, Json, GIT, Rest API, and Azure Resource Management (ARM) templates to build and manage CI/CD pipelines. Implemented standards and best practices for the CI/CD framework, including version control, code review, and testing.Used security scanning/monitoring tools to ensure code is free from vulnerabilities and integrated these tools with the CI/CD pipeline. Collaborated with development teams to troubleshoot issues and debug code on Windows environments.Provided guidance to junior engineers on best practices for CI/CD pipelines and cloud-native architectures. Used Spark Streaming to divide streaming data into batches as an input to Spark engine for batch processing. Creating Amazon EC2 instances using command line calls and troubleshoot the most common problems with instances and monitor the health of Amazon EC2 instances and other AWS services.Developed rest API's using python with flask and Django framework and done the integration of various data sources including Java, JDBC, RDBMS, Shell Scripting, Spreadsheets, and Text files. Involved in designing and deploying multi-tier applications using all the AWS services like (EC2, Route53, S3, RDS, Dynamo DB, SNS, SQS, IAM) focusing on high-availability, fault tolerance, and auto-scaling in AWS Cloud Formation.Utilized Apache Spark with Python to develop and execute Big Data Analytics and Machine learning applications, executed machine Learning use cases under Spark ML and MLlib.

El Dorado Hills, California, Us

Participated in the analysis, design, and development phase of the Software Development Lifecycle (SDLC). Experience in the agile environment, used to have sprint planning meeting, scrum calls and retro meetings for every sprint, Used JIRA for the project management and GitHub for the version control.Design, develop and maintain non-production and production transformations in Azure environment and create the data pipelines using PySpark Programming, using Spark, Hive, Pig, python, Impala, and HBase to ingest customer DB.Used Spark Streaming to divide streaming data into batches as an input to Spark engine for batch processing. Wrote Spark applications for data validation, cleansing, transformation, and custom aggregation and used Spark engine, Spark SQL for data analysis and provided to the data scientists for further analysis.Developed rest API's using python with flask and Django framework and done the integration of various data sources including Java, JDBC, RDBMS, Shell Scripting, Spreadsheets, and Text files. Utilized Apache Spark with Python to develop and execute Big Data Analytics and Machine learning applications, executed machine Learning use cases under Spark ML and MLlib.Developed Spark, Python for regular expression (regex) project in the Hadoop/Hive environment with Linux/Windows for big data resources.Profile structured, unstructured, and semi-structured data across various sources to identify patterns in data and Implement data quality metrics using necessary queries or python scripts based on source.Analyze, design, and build Modern scalable distributed data solutions using with Hadoop, Azure cloud services.

Copenhagen, Capital Region Of Denmark, Dk

Participated in the analysis, design, and development phase of the Software Development Lifecycle (SDLC). Experience in the agile environment, used to have sprint planning meeting, scrum calls and retro meetings for every sprint, Used JIRA for the project management and GitHub for the version control.Extensively used PySpark to implement transformations and deployed in Azure HDInsight for ingestion and Hygiene, Identity Resolution process.Worked on creating a File based Data Lake using Azure Blob Storage, Azure Data Factory, Azure HDInsight. used HBase to Data Storage and Retrieval.Developed Pipelines for batch processing and scheduling using Azure Data Factory.Created Azure ML studio pipeline with python module codes to execute the Naive bayes and boost classification (machine learning algorithm) for persona Mapping.Loaded data (ingestion) from Salesforce, SAP, SQL server, Teradata to Azure Data Lake using Azure Data Factory.Worked on Implementing Business rules for deduplication of contacts by using spark transformations with spark python and PySpark. Involved in designing and deploying multi-tier applications using all the AWS services like (EC2, Route53, S3, RDS, Dynamo DB, SNS, SQS, IAM) focusing on high-availability, fault tolerance, and auto-scaling in AWS Cloud Formation.Developed Graph Database nodes and relation using cypher language. Developed spark job using Spark Data frames to flatten Jon documents to flat file.Developed micro services using AWS Lambda to make API calls for third party vendors like Melissa, Strike iron.Involved in supporting cloud instances running Linux and Windows on AWS, experience with Elastic IP, Security Groups and Virtual Private Cloud in AWS.

Fremont, California, Us

Played a key role in gathering business requirements, system and design requirements, gap analysis, use case diagrams and flow charts. Built single page, cross-device/cross- browser/mobile friendly web dashboard using Angular JS thatallows to build, manage multiple chatbots across various environments.Developed the Bot framework conversation flows using NODE-RED, NodeJS, MS Bot framework and web dashboard’s User Interface using HTML, CSS, Bootstrap and Angular JS.Developed custom nodes on NODE-RED dashboard for building conversations using Node.js over MS botframework.Actively involved in building user authentication for the application using Storm path and passportjs.Implemented various Validation Controls for client-side validation and implemented custom validationcontrols with Angular validation controls and Angular Material Design.Developed Spark applications using PySpark and Spark-SQL for data extraction, transformation, andaggregation from multiple file formats for analyzing & transforming the data to uncover insights into thecustomer usage patterns.