Likhita B

• Design and implement database solutions in Azure SQL Data Warehouse, Azure SQL.
• Architect & implement medium to large scale BI solutions on Azure using Azure Data Platform services (Azure Data Lake, Data Factory, Data Lake Analytics, Stream Analytics, Azure SQL DW, HDInsight/Databricks, NoSQL DB).
• Design & implement migration strategies for traditional systems on Azure (Lift and shift/Azure Migrate, other third-party tools.
• Developed Json Scripts for deploying the Pipeline in Azure Data Factory (ADF) that process the data using the Cosmos Activity
• Engage with business users to gather requirements, design visualizations and provide training to use self-service BI tools.
• Build data pipelines in airflow in GCP for ETL related jobs using different airflow operators
• Develop Snow SQL code for data manipulation, Extraction, and Loading (ETL) processes.

Design and implement database solutions in Azure SQL Data Warehouse, Azure SQL.
Architect & implement medium to large scale BI solutions on Azure using Azure Data Platform services (Azure Data Lake, Data Factory, Data Lake Analytics, Stream Analytics, Azure SQL DW, HDInsight/Databricks, NoSQL DB).
Design & implement migration strategies for traditional systems on Azure (Lift and shift/Azure Migrate, other third-party tools.
Developed Json Scripts for deploying the Pipeline in Azure Data Factory (ADF) that process the data using the Cosmos Activity
Engage with business users to gather requirements, design visualizations and provide training to use self-service BI tools.
Build data pipelines in airflow in GCP for ETL related jobs using different airflow operators
Develop Snow SQL code for data manipulation, Extraction, and Loading (ETL) processes.
Use various sources to pull data into Power BI such as SQL Server, Excel, Oracle, SQL Azure etc.
Propose architectures considering cost/spend in Azure and develop recommendations to right-size data infrastructure.
Involved in running the Cosmos Scripts in Visual Studio 2017/2015 for checking the diagnostics
Designed and implemented ETL processes using IBM InfoSphere DataStage for data integration and transformation.
Integrated streaming data sources into data lakes and data warehouses for comprehensive analysis.
Designed and implemented data pipelines using Azure Synapse for scalable and efficient data processing.
Used Cosmos DB for storing catalog data and for event sourcing in order processing pipelines.
Designed and developed user defined functions, stored procedures, triggers for Cosmos DB
Validated the Hadoop jobs like MapReduce, Oozie using CLI. Able to handle the jobs in HUE too.
Organized, participated and governed the requirements sessions involving stakeholders from sponsors, business, operations groups and technology teams, and provided guidance to detail out scoped requirements, Influenced and negotiated effectively for harmonized conclusions on scope creeps
Wrote various data normalization jobs for new data ingested into Redshift.
Experience in moving data between GCP and Azure using Azure Data Factory
Collaborate with application architects and DevOps.
Used the AWS-CLI to suspend an AWS Lambda function processing an Amazon Kinesis stream, then to resume it again
Identify and implement best practices, tools and standards.
Draft daily hedge strategy reports detailing market analysis, adjusted portfolio coverage and executed trades during the day to brief the Director of Capital Markets and COO/CAO of the organization
Extensive experience in Apachi/Hudi Datasets on Insert /Bulk insert
Design Setup maintain Administrator the Azure SQL Database, Azure Analysis Service, Azure SQL Data warehouse, Azure Data Factory, Azure SQL Data warehouse.
Create several types of data visualizations using Python and Tableau.
Build Complex distributed systems involving huge amount data handling, collecting metrics building data pipeline, and Analytics.
Utilized Azure Synapse SQL and Spark pools for both relational and big data processing requirements.
Orchestrated and scheduled ETL workflows using Apache Airflow for streamlined data processing.
Develop conceptual solutions & create proof-of-concepts to demonstrate viability of solutions.
Prepared the project proposals, including scope analysis, Future state, cost estimates, terms of reference and cost/benefit studies for the new applications.
Use Python and Django creating graphics, XML processing, data exchange and business logic implementation
Technically guide projects through to completion within target timeframes.

Designed and developed Security Framework to provide fine grained access to objects in AWS S3 using AWS Lambda, DynamoDB.
Designed and developed applications using Apache Spark, Scala, NiFi, S3, AWS EMR on AWS cloud to format, cleanse, validate, create schema and build data stores on S3.
Worked with Linux systems and RDBMS database on a regular basis in order to ingest data using Sqoop.
Created a Lambda function to run the AWS Glue job based on the AWS S3 event.
Used AWS data pipeline for Data Extraction, Transformation and Loading from homogeneous or heterogeneous data sources and built various graphs for business decision-making using Python Matplot library.
Populated HDFS and PostgreSQL with huge amounts of data using Apache Kafka.
Designed and developed Rest API (Commerce API) which provides functionality to connect to the PostgreSQL through Java services.
Implemented data pipelines using PySpark on distributed computing clusters to handle big data workloads.
Designed and implemented Snowflake data warehouses for efficient storage and retrieval of structured and semi-structured data.
Implemented dynamic DAGs for parameterized and reusable ETL processes, reducing development time and enhancing maintainability.
Used various AWS services including S3, EC2, AWS Glue, Athena, RedShift, EMR, SNS, SQS, DMS, Kenesis.
Migrated on premise database structure to Confidential Redshift data warehouse.
Designed Batch Audit Process in batch/shell script to monitor each ETL job along with reporting status which includes table name, start and finish time, number of rows loaded, status, etc.
Developed entire frontend and backend modules using Python on Django Web Framework.
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.
Used Amazon EMR for MapReduce jobs and test locally using Jenkins.
Responsible for continuous monitoring and managing Elastic MapReduce (EMR) cluster through AWS console.
Designed and implemented data acquisition, ingestion, Management of Hadoop infrastructure and other Analytics tools (Splunk, Tableau).
Developed PySpark scripts for large-scale data processing, transformation, and analysis.
Used AWS glue catalog with crawler to get the data from S3 and perform SQL query operations using AWS Athena.
Used MongoDB to stored data in JSON format and developed and tested many features of dashboard using Python, Bootstrap, CSS, and JavaScript.
Built various graphs for business decision making using Python matplotlib library.
Working knowledge of build automation and CI/CD pipelines.
Developed scripts to automate data ingestion pipeline for multiple data sources and deployed Apache NiFi in AWS.
Designed and developed Tableau visualizations which include preparing Dashboards using calculations, parameters, calculated fields, groups, sets and hierarchies.

Performed Data Integration, Extraction, Transformation, and Load (ETL) Processes in preprocessing phase, used Pandas to remove or replace all the missing data and balanced the dataset with Over-sampling the minority label class and Under-sampling the majority label class to perform a well Data Cleaning Process.
Developed Rest API to serve the data generated by prediction model to serve other customers/teams.
Generated complex reports in various formats such as list reports, summary reports etc. using advanced data manipulation techniques from SAS Enterprise Guide.
Analyzed data and generated analytical reports using SAS, MS SQL.
Implemented code in Python to retrieve and manipulate data.
Designed and Developed ETL jobs to extract data from Salesforce replica and load it in data mart in Redshift.
Developed models relying on Linear Regression, Multiple Regression, Decision Trees, Random Forest, Logistic Regression, Naive Bayes.
Optimized PySpark jobs for performance by tuning configurations and leveraging appropriate caching strategies.
Built Complex distributed systems involving huge amount data handling, collecting metrics building data pipeline, and Analytics.