Meenal Shukla

• Consulted regularly with internal customers on application development project status, new project proposals and software-related technical issues.
  Interfaced with cross-functional team of business analysts, developers and technical support professionals to determine comprehensive list of requirement specifications for new applications.
  Managed talented teams in various organisation over 2 projects.
  Contributed to development of integration tools to combine data from multiple, varied data sources such as file system CSV, AVRO and API as Data Source for big data installations.
  Developer RESTFul web services
  Collaborated on all stages of systems development lifecycle, from requirement gathering to production releases.
  Debugged legacy application & improved understanding of Business requirement.
  Contributed ideas and suggestions in team meetings and delivered updates on deadlines, designs and enhancements.
  Capturing telemetry data from various sources and pushing it in Snowflake.
  Data is received in various forms like JSON , AVRO , API which is then placed in cloud .
  Process and Flattened of schema into a uniform format based on version of device end system . This is cataloging.
  Ingest data based on cataloged schema into Snowflake.
  Utilized telemetry equipment to closely monitor vital signs and quickly identify any abnormalities or potential complications.

For application teams,
Design pipelines to load data from CosmosDB to SQL Server and vice versa for historical data, as well as data sync pipelines to sync data between different systems.
Implemented data transformation through Spark batch processing.
Developed and implemented performance improvement strategies and plans to promote continuous improvement.
Collaborated on ETL (Extract, Transform, Load) design, implementation, and maintenance of data integrity, and verifying pipeline stability.
Deriving analysis on various use cases for post-audit purposes in SQL, and projecting them in a Tableau dashboard.
Migrated on-prem SQL Server data warehouse to BigQuery.
For the Data Team.
Migrated legacy systems to modern big-data technologies, improving performance and scalability, while minimizing business disruption.
Streamlined complex workflows by breaking them down into manageable components for easier implementation and maintenance.
Designing and building a generic ELT pipeline, which can be reused for various data source ingestions to BigQuery using GCP and custom code.
Contributed to building a streaming pipeline with Kafka and Spark batch processing.
Conducted extensive troubleshooting to identify the root causes of issues and implement effective resolutions in a timely manner, using CI/CD orchestration tools like Airflow.
Agentic AI-
Reengineered existing ETL workflows to improve performance by identifying bottlenecks and optimizing code accordingly.
Currently, I am trying to build an automated version of the building pipeline based on our current implementation using Agentic AI.
The target is to reduce man-hours in creating a new pipeline and help them build ETL.