Devendra Reddy Email & Phone Number

• Worked on AWS Data pipeline to configure data loads from S3 to into Redshift.• Using AWS Redshift, I Extracted, transformed and loaded data from various heterogeneous data sources and destinations• Created Tables, Stored Procedures, and extracted data using T-SQL for business users whenever required.• Performs data analysis and design, and creates and maintains large, complex logical and physical data models, and metadata repositories using ERWIN and MB MDR• I have written shell script to trigger data Stage jobs.• Assist service developers in finding relevant content in the existing reference models.• Like Access, Excel, CSV, Oracle, flat files using connectors, tasks and transformations provided by AWS Data Pipeline.• Utilized Spark SQL API in PySpark to extract and load data and perform SQL queries.• Worked on developing Pyspark script to encrypting the raw data by using Hashing algorithms concepts on client specified columns.• Responsible for Design, Development, and testing of the database and Developed Stored Procedures, Views, and Triggers• Developed Python-based API (RESTful Web Service) to track revenue and perform revenue analysis.• Compiling and validating data from all departments and Presenting to Director Operation.• KPI calculator Sheet and maintain that sheet within SharePoint.• Created Tableau reports with complex calculations and worked on Ad-hoc reporting using PowerBI.• Creating data model that correlates all the metrics and gives a valuable output.• Worked on the tuning of SQL Queries to bring down run time by working on Indexes and Execution Plan.• Performing ETL testing activities like running the Jobs, Extracting the data using necessary queries from database transform, and upload into the Data warehouse servers.• Extract Transform and Load data from Sources Systems to Azure Data Storage services using a combination of Azure Data Factory, T-SQL, Spark SQL, and U-SQL Azure Data Lake Analytics.

• Implemented Apache Airflow for authoring, scheduling and monitoring Data Pipelines• Designed several DAGs (Directed Acyclic Graph) for automating ETL pipelines• Performed data extraction, transformation, loading, and integration in data warehouse, operational data stores and master data management• Strong understanding of AWS components such as EC2 and S3• Performed Data Migration to GCP• Responsible for data services and data movement infrastructures• Experienced in ETL concepts, building ETL solutions and Data modeling• Worked on architecting the ETL transformation layers and writing spark jobs to do the processing.• Loaded application analytics data into data warehouse in regular intervals of time• Designed & build infrastructure for the Google Cloud environment from scratch• Experienced in fact dimensional modeling (Star schema, Snowflake schema), transactional modeling and SCD (Slowly changing dimension)• Leveraged cloud and GPU computing technologies for automated machine learning and analytics pipelines, such as AWS, GCP• Worked on confluence and Jira• Designed and implemented configurable data delivery pipeline for scheduled updates to customer facing data stores built with Python• Proficient in Machine Learning techniques (Decision Trees, Linear/Logistic Regressors) and Statistical Modeling• Compiled data from various sources to perform complex analysis for actionable results• Measured Efficiency of Hadoop/Hive environment ensuring SLA is met• Optimized the Tensorflow Model for efficiency• Analyzed the system for new enhancements/functionalities and perform Impact analysis of the application for implementing ETL changes• Implemented a Continuous Delivery pipeline with Docker, and Git Hub and AWS• Built performant, scalable ETL processes to load, cleanse and validate data• Preparing associated documentation for specifications, requirements, and testing

• Experience in building and architecting multiple Data pipelines, end to end ETL and ELT process for Data ingestion and transformation in GCP• Strong understanding of AWS components such as EC2 and S3• Implemented a Continuous Delivery pipeline with Docker and Git Hub• Process and load bound and unbound Data from Google pub/sub topic to Bigquery using cloud Dataflow with Python.• Devised simple and complex SQL scripts to check and validate Dataflow in various applications.• Developed and deployed data pipeline in cloud such as AWS and GCP• Responsible for data services and data movement infrastructures good experience with ETL concepts, building ETL solutions and Data modeling• Architected several DAGs (Directed Acyclic Graph) for automating ETL pipelines• Hands on experience on architecting the ETL transformation layers and writing spark jobs to do the processing.• Gather and process raw data at scale (including writing scripts, web scraping, calling APIs, write SQL queries, writing applications)• Experience in fact dimensional modeling (Star schema, Snowflake schema), transactional modeling and SCD (Slowly changing dimension)• Devised PL/SQL Stored Procedures, Functions, Triggers, Views and packages. Made use of Indexing, Aggregation and Materialized views to optimize query performance.• Hands of experience in GCP, Big Query, GCS bucket, G - cloud function, cloud dataflow, Pub/suB cloud shell, GSUTIL, BQ command line utilities, Data Proc, Stack driver• Implemented Apache Airflow for authoring, scheduling and monitoring Data Pipelines• Proficient in Machine Learning techniques (Decision Trees, Linear/Logistic Regressors) and Statistical Modeling• Worked on confluence and Jira skilled in data visualization like Matplotlib and seaborn library• Hands on experience with big data tools like Hadoop, Spark, Hive• Experience implementing machine learning back-end pipeline with Pandas, Numpy

Dorchester, Massachusetts, United States

• Imported required modules such as Keras and NumPy on Spark session, also created directories for data and output.• Read train and test data into the data directory as well as into Spark variables for easy access and proceeded to train the data based on a sample submission.• The images upon being displayed are represented as NumPy arrays, for easier data manipulation all the images are stored as NumPy arrays.• Created a validation set using Keras2DML in order to test whether the trained model was working as intended or not.• Defined multiple helper functions that are used while running the neural network in session. Also defined placeholders and number of neurons in each layer.• Created neural networks computational graph after defining weights and biases.• Created a TensorFlow session which is used to run the neural network as well as validate the accuracy of the model on the validation set.• After executing the program and achieving acceptable validation accuracy a submission was created that is stored in the submission directory.• Executed multiple SparkSQL queries after forming the Database to gather specific data corresponding to an image.

Hyderabad, Telangana, India

• Used Test driven approach for developing the application and Implemented the unit tests using Python Unit test framework.• Migrated successfully the Django database from SQLite to MySQL to PostgreSQL with complete data integrity.• Worked on report writing using SQL Server Reporting Services (SSRS) and in creating various types of reports like table, matrix, and chart report, web reporting by customizing URL Access.• Developed views and templates with Python and Django's view controller and templating language to create a user-friendly website interface.• Performed API testing by utilizing POSTMAN tool for various request methods such as GET, POST, PUT, and DELETE on each URL to check responses and error handling.• Created Python and Bash tools to increase efficiency of retail management application system and operations; data conversion scripts, AMQP/Rabbit MQ, REST, JSON, and CRUD scripts for API Integration.• Performed debugging and troubleshooting the web applications using Git as a version-controlling tool to collaborate and coordinate with the team members.• Developed and executed various MySQL database queries from python using python -MySQL connector and MySQL database package.• Designed and maintained databases using Python and developed Python based API (RESTful Web Service) using SQL Alchemy and PostgreSQL.• Created a web application using Python scripting for data processing, MySQL for the database, and HTML CSS, jQuery and High Charts for data visualization of the served pages.• Generated property list for every application dynamically using Python modules like math, glob, random, itertools, functools, NumPy, matplotlib, seaborn and pandas.• Added the navigations and paginations and filtering columns and adding and removing the desired columns for view utilizing Python based GUI components.