Priyanka S Email and Phone Number

• Building Reusable Data ingestion and Data transformation frameworks using Python• Write Terraform scripts to automate AWS services which include ELB, CloudFront• Extensively used Kubernetes and Docker for the runtime environment• Configure and optimize Hudi datasets for efficient data processing and storage.• Configured documents which allow Airflow to communicate to its PostgreSQL database.• Collaborate with the team to ensure proper integration and utilization of Hudi for real-time data processing.• Experience in the design, development and deployment of Analytical and Business Intelligence solutions using Big Data technologies Hive, PySpark, SSRS.• Assisted in designing & developing Data Lake and ETL using Python and Hadoop ecosystem• Implement AWS Elastic Container Service (ECS) scheduler to automate application deployment in the cloud using Docker Automation techniques.• Documented and communicated Hudi implementation details, ensuring clear and comprehensive documentation for the client's reference and future use.• Troubleshoot data issues in HANA and Tableau reports.• Worked on implementing Data warehouse solutions in AWS Redshift, worked on various projects to migrate data from one database to AWS Redshift, Glue, RDS, ELB, EMR, DynamoDB and S3 Perform data profiling, cleansing, and data governance on major data flows.• Worked on Oracle Databases, RedShift, PostgreSQL, Snowflakes.• Used ReactJS/AngularJS for templating for faster compilation and developing reusable components.• Architect and configure a virtual data center in the AWS cloud to support Enterprise Data Warehouse hosting including Virtual Private Cloud (VPC), Public and Private Subnets, Security Groups and Route Tables.• Implemented stable ReactJS/AngularJS components and functions• Web application to provide online. (Ruby on Rails, JavaScript, PostgreSQL, CSS, html, Ajax, soap)

• Involved in all phases of SDLC (Software Development Life Cycle) right from requirement gathering and participated in meetings with business users along with business analysts.• Programmatically created CI/CD Pipelines in Jenkins using Groovy scripts. • Wrote various data normalization jobs for new data ingested into Redshift.• Used Kubernetes to deploy scale, load balance, scale and manage docker containers with multiple names spaced versions.• Design Setup maintain Administrator the Azure SQL Database, Azure Analysis Service, Azure SQL Data warehouse, Azure Data Factory, Azure SQL Data warehouse.• Managed Logical and Physical Data Models in ER Studio Repository based on the different subject area requests for integrated model. Developed Data Mapping, Data Governance, and transformation and cleansing rules involving OLTP, ODS.• Developed JSON Scripts for deploying the Pipeline in Azure Data Factory (ADF) that process the data using the SQL Activity.• Used JSON schema to define table and column mapping from S3 data to Redshift.• Good understanding of Big Data Hadoop and Yarn architecture along with various Hadoop Demons such as Job • Tracker, Task Tracker, Name Node, Data Node, Resource/Cluster Manager, and Kafka (distributed stream processing).• Responsible for migrating the database into AWS Redshift.• Used Apache Airflow in Azure composer environment to build data pipelines and used various airflow operators like bash operator, Hadoop operators and Python callable and branching operators.• Worked with Terraform Templates to automate the Azure IaaS virtual machines using terraform modules and • deployed virtual machine scale sets in production environment.• Developed spark applications in Python (PySpark) on distributed environment to load huge number of CSV files with different schema in to Hive ORC tables.• Integrated Azure Log Analytics with Azure VMs for monitoring the log files, store them.

• Involved in the entire project life cycle, from design discussions to production deployment.• Developing Web Application in Groovy/Grails with MongoDB as a data stores. • Provide guidance to development team working on PySpark.• Involved in designing the Data pipeline from end-to-end, to ingest data into the Data Lake• Extensive working experience using JIRA, ALM.• Developed file cleaners using Python libraries and made it clean.• Created several Databricks Spark jobs with PySpark to perform several tables to table operations.• Followed Agile Methodologies while working on the project• Developed SSIS packages to ETL data into heterogeneous data warehouses.