Naveen Kumar Manukonda

Hands-on experience in designing, planning, and implementing the migration of existing on-premise applications to
the Azure Cloud using Azure Resource Manager (ARM)
• Configured and deployed Azure Automation Scripts utilizing various Azure stack services and utilities with a focus on
automation
• Implemented storage blobs and Azure files, created storage accounts, configured the Content Delivery Network
(CDN), and managed access and storage access keys
• Expertise in Windows Azure Services, including Platform as a Service (PaaS) and Infrastructure as a Service (IaaS), and
extensive work on storages like Blob (Page and Block), and Sql Azure
• Proficient in deployment and configuration management, as well as virtualization

• Developed and supported Software Release Management and procedures, working with Subversion and
proposing/implementing branching strategies
Knowledge on configuring single sign-on (SSO) and multi-factor authentication (MFA) for enhanced security
• Skilled in integrating Azure Active Directory with various applications and services for centralized identity
management
• Utilized Docker for setting up Azure Container Registry, Docker, and Docker-compose, actively involved in deployments
on Docker using Kubernetes
• Used Azure Kubernetes Service for deploying managed Kubernetes clusters and leveraged templatedriven
deployment options such as Resource Manager templates and terraform
• Configured servers to host Team Foundation Server (TFS) instances for setting up and managing Continuous
Integration (CI) using Team Foundation (TF) Build Service
• Assisted with the installation, upgrade, and troubleshooting of JAWS and AutoSys as well as with the documentation
and procedures
• Helm-managed charts in Kubernetes
• Created repeatable builds of the Kubernetes applications, templated Kubernetes manifests, provided a set of
configuration settings to modify the deployment, and Helm package releases that have been carefully controlled
• Used AWS Beanstalk for deploying and scaling web applications and services developed with Java, PHP, Node.js,
Python, Ruby, and Docker on familiar servers such as Apache, and IIS
• Architecture/design and deployment of solutions using VMWare, Azure and Amazon Web Services (AWS)
• Production-ready Kubernetes cloud architecture with microservice container orchestration that is load-balanced,
highly available, fault-tolerant, and auto-scaling was implemented
• Integrated Azure Data Factory with various Azure services such as Azure Databricks, Azure Machine Learning, and
Azure HDInsight for holistic data processing and analytics
• Implemented trigger-based execution to automate pipeline runs based on events or schedules, enhancing operational
efficiency
• Experienced in defining file systems, directories, and access controls within Azure Data Lake Storage for efficient
• Knowledge on using tools like Azure Storage Explorer and Azure CLI to interact with and manage data lake resources
• Integrated with a variety of data sources, including Azure SQL Database, Azure Blob Storage, and onpremises SQL
Server, ensuring comprehensive connectivity
• Created clusters using Kubernetes and worked on authoring Yaml files to create several pods, replication controllers,
replica sets, services, deployments, labels, health checks, and ingress Working understanding of Docker Hub, Docker
Container network, and generating Image files largely for middleware installations and domain setups Use Kubernetes
for orchestrating Docker containers
• Participated in the development of the architecture and constructed the Minimum Viable Product (MVP) for the
Docker and Kubernetes containerization platform
• Experience in Performance Tuning and Query Optimization in AWS Redshift
• Managed Amazon Redshift clusters such as launching the cluster and specifying the node type
• Involved in creating a test environment using Docker containers and setting up the Kubernetes container in a Docker
container
• Worked on optimizing query performance by fine-tuning distributed query execution and indexing strategies
• Implemented seamless data integration with Azure Synapse Analytics, incorporating data from diverse sources for
unified analytics
• Integrated Azure Synapse Analytics seamlessly with Power BI for creating compelling data visualizations and reports
• Created Puppet Manifests and modules to automate system operations
• Responsible for delivering an end-to-end continuous integration - continuous delivery system for the products in an
agile development approach using Puppet and Jenkins
• Built Continuous Integration environment Jenkins, Artifactory and Continuous delivery environment using Jenkins,
Yum and Puppet
• Used Maven to build rpms from source code checked out from GIT and Subversion repository, with Jenkins being the
Continuous Integration Server and Artifactory as repository manager
• Environment: IAM, Redshift, Lambda, VPC, Chef, Java, Git, Jenkins, Terraform, Python, Linux, Bash,
Groovy, Subversion, Rest API, Ant, Maven, Nexus, U-deploy, SQL, Cloud Formation, Open Shift, Cassandra, Subversion,
Selenium, UNIX, SVN, Docker, Jira, Python, Ruby, Shell Scripts, Tomcat, Ansible, Splunk.

Designed and developed scalable and cost-effective architecture in AWS Big Data services for data life cycle of
collection, ingestion, storage, processing, and visualization.
 Involved in creating End-to-End data pipeline within distributed environment using the Big data tools, Spark
framework and Tableau for data visualization.
 Ensure that application continues to function normally through software maintenance and testing in production
environment.
 Leverage Spark features such as In-Memory processing, Distributed Cache, Broadcast, Accumulators, Map side
Joins to implement data preprocessing pipelines with minimal latency.
 Implemented real-time solutions for Money Movement and transactional data using Kafka, Spark Streaming, Hbase.
 The project also includes a spread of big data tools and programming languages like Sqoop, Scala, Python,
Oozie etc.
 Worked on scheduling Oozie workflow engine to run multiple jobs.
 Experience in creating python topology script to generate cloud formation template for creating the EMR cluster in
AWS.
 Good knowledge on AWS Services like EC2, EMR, S3, Service Catalog, and Cloud Watch.
 Experience inusingSparkSQL to handle structured data fromHive in AWSEMR Platform (M4.Xlarge,M5.12Xlarge
clusters).
 Exploring with Spark, improving performance and optimization of the existing algorithms in Hadoop using Spark
Context, Spark-SQL, Data Frame, and Pair RDD's.
 Experienced in handling large datasets using Partitions, Spark in Memory capabilities, Broadcasts in Spark, Effective
& efficient Joins, Transformations and other during ingestion process itself.
 Experienced in optimizing Hive queries, joins to handle different data sets.
 Involved in creating Hive tables (Managed tables and External tables), loading and analyzing data using hive queries.
 Actively involved in code review and bug fixing for improving the performance.
 Good experience in handling data manipulation using python Scripts.
 Involved in development, building, testing, and deploy to Hadoop cluster in distributed mode.
 Created Splunk dashboard to capture the logs for end to end process of data ingestion.
 Written unit test cases for Spark code for CICD process.
 Good knowledge about the configuration management tools like BitBucket/Github and Bamboo(CICD).

Environment: AWS EMR, Attunity, Kinesis, DynamoDB, SNS, SQS, CloudWatch, HDFS, Sqoop, LINUX, Oozie,
Hive, Spark, Kafka, SparkStreaming,Scala, Python, Tableau,MongoDB, Amazon Web Services, Talend.

Experience with professional software engineering practices and best practices for the full software
development life cycle including coding standards, code reviews, source control management and build
processes.
 Worked on analyzing Hadoop cluster and different big data analytic tools including Map Reduce, Hive.
 Written multiple MapReduce programs for data extraction, transformation and aggregation from multiple
file formats including XML, JSON, CSV & other compressed file formats.

 Worked on Teradata parallel transport (TPT) to load data from databases and files to Teradata.
 Wrote views based on user and/or reporting requirements.
 Wrote Teradata Macros and used various Teradata analytic functions.
 Involved in migration projects to migrate data from data warehouses on Oracle/DB2 and migrated those to
Teradata.
 Configured Flume source, sink and memory channel to handle streaming data from server logs and JMS
sources.
 Experience in working with Flume to load the log data from multiple sources directly into HDFS.
 Worked in the BI team in Big Data Hadoop cluster implementation and data integration in developing
large-scale system software.
 Involved in source system analysis, data analysis, data modeling to ETL (Extract, Transform and Load).
 Handling structured and unstructured data and applying ETL processes.
 Worked extensively with Sqoop for importing and exporting the data from HDFS to Relational Database
systems/mainframe and vice-versa. Loading data into HDFS.
 Involved in collecting, aggregating and moving data from servers to HDFS using Flume.
 Implemented logging framework – ELK stack (Elastic Search, LogStash& Kibana) on AWS.
 Developed the Pig UDF’S to pre-process the data for analysis.
 Coding complex Oracle stored procedures, functions, packages, and cursors for the client specific
applications.
 Experienced in using Java Rest API to perform CURD operations on HBase data.
 Applied Hive queries to perform data analysis on HBase using Storage Handler to meet the business
requirements
 Writing Hive Queries to Aggregate Data that needs to be pushed to the HBase Tables.
 Create/Modify shell scripts for scheduling various data cleansing scripts and ETL loading process.
 Supports and assist QA Engineers in understanding, testing and troubleshooting.

Environment:Hadoop, Hive, Linux, Map Reduce, Sqoop, Storm, HBase, Flume, Eclipse, Maven, Junit, agile
methodologies.

Review the system requirements and attending requirements meetings with analysts and users.
 Involved in the life cycle of the project from documentation to unit testing making development as
priority.
 Developed web pages using Struts framework, JSP, XML, JavaScript, HTML/ DHTML and CSS, configure
struts application, use tag library.
 Used Apache Struts framework includes the integrated AJAX.
 Played major role in designing & developing JSP pages and XML reports.
 Developed Servlets and custom tags for JSP pages.
 Developed few module Web pages using Springs IOC and Hibernate.
 Designed and developed dynamic pages using HTML, CSS- layout techniques, Java script.
 Took the various challenges in the enhancement and completed them on time.

 Extensive Used Exception handling and Multi-threading for the optimum performance of the application.
 Involved in design and implemented (SOA, SOAP) next generation system on distributed platform.
 Extensively used XSL as a XML parsing mechanism for showing Dynamic Web Pages in HTML format.
 Implemented SOAP protocol to get the requests from the outside System.
 Used CVS as a source control for code changes.
 Used ANT scripts to build the project and JUnit to develop unit test cases.
 Developed coding using SQL, PL/SQL, Queries, Joins, Views, Procedures/Functions, Triggers and Packages.
 Provided development support for System Testing, Product Testing, User Acceptance Testing, Data
Conversion Testing, Load Testing, and Production.

Environment: Java 1.5, J2EE, AJAX, Servlets, JSP, RUP, Eclipse 3.1, Struts, Spring 2.0, Hibernate, XML, CVS, Java
Script, JQuery, ANT, SOAP, Log4J, DB2, Web Sphere server, UNIX, IBM Web Sphere Portal Server