GOVARTHANAGIRI

Innovative Data Engineer with over 3.6 years of experience at Agilisum Consulting and a Bachelor of Engineering degree. Proficient in Python, SQL, PySpark, AWS, MuleSoft, Databricks, and a variety of databases. Adept at designing scalable data pipelines and integration solutions. Committed to delivering high-impact, results-driven solutions through collaboration, innovation, and technical excellence.

AWS Certified Cloud Practitioner

Project #1: MDM-CRM INTEGRATION

Client: AMGEN

Duration: Mar 2022 – JAN 2023.

Environment: MULESOFT,DATABRICKS

Description:

This project involved developing and managing MuleSoft applications to synchronize data between Master Data Management (MDM) and Customer Relationship Management (CRM) systems. The integration covered both outbound flows, including Data Change Request (DCR) and Consent processes, and inbound flows from five different source applications into the CRM system. The MuleSoft-based solution ensured seamless, reliable, and real-time data exchange, maintaining data consistency, compliance, and accuracy across both platforms.

Key Duties and Responsibilities:

• Developed and enhanced MuleSoft applications for data integration between MDM and CRM systems.
• Assisted in designing and implementing data transformation logic within MuleSoft flows.
• Monitored inbound and outbound jobs to ensure smooth execution.
• Conducted unit testing and supported deployment on CloudHub using CI/CD pipelines.
• Collaborated with the team and communicated with clients for requirement clarification and progress updates.
• Validated data accuracy between source and target systems to ensure consistency.
• Contributed to team meetings by providing updates on development progress and enhancements.

Project #2:ATLAS INTEGRATION

Client: AMGEN

Duration: JAN 2023 to DEC 2023.

Environment: MULESOFT,DATABRICKS,S3

Description:

This project involved building a hybrid data pipeline combining PySpark and MuleSoft technologies. The PySpark process extracted and transformed data from multiple source systems, loading it into Databricks Delta tables, MySQL databases, and Amazon S3 for further use. The MuleSoft application then consumed the transformed data from S3 to load it into Salesforce, ensuring seamless synchronization and data consistency across platforms. The solution optimized data workflows, automated transformations, and enabled efficient integration between diverse systems.

Key Duties and Responsibilities:

• Designed and developed MuleSoft applications and data transformation logic.
• Developed complex queries for ETL processes and built new pipelines based on client requirements.
• Conducted unit testing and managed deployments on CloudHub using CI/CD pipelines.
• Ensured data synchronization between systems.
• Participated in requirement gathering and collaborated with the team to provide progress updates.
• Contributed to team meetings by providing updates on development progress and enhancements.

Project #3:OCX to Salesforce Integration

Client: AMGEN

Duration: OCT 2023 to DEC 2023.

Environment: MULESOFT,S3

Description:

This project automates and streamlines the extraction of files from Amazon S3 and the subsequent loading of data into Salesforce. Leveraging MuleSoft’s robust integration capabilities, the solution ensures efficient, secure, and accurate data transfer, creating a seamless and reliable data pipeline between S3 and Salesforce.

Key Duties and Responsibilities:

• Designed and developed MuleSoft applications to automate data extraction from Amazon S3 and loading into Salesforce.
• Implemented data transformation and validation logic to ensure data accuracy and integrity.
• Managed deployment of MuleSoft applications on CloudHub with CI/CD pipelines.
• Conducted unit testing and troubleshooting to ensure seamless data flow and error handling.
• Monitored integration jobs and performed regular maintenance to optimize performance and reliability.
• Provided regular updates to the team and coordinated with clients to ensure alignment with business needs.

Project #4:MULTIOMICS

Client: AMGEN

Duration: JUL 2023 – APR 2024.

Environment: MULESOFT

Description:

The MuleSoft API Integration project is designed to streamline and enhance data retrieval by seamlessly connecting with external APIs. Leveraging MuleSoft’s capabilities, this solution enables efficient real-time data fetching from external sources and delivers the data in a well-structured, consumable format.

Key Duties and Responsibilities:

• Developed APIs using RAML and built MuleSoft applications based on business requirements.
• Designed and implemented data transformation logic within MuleSoft.
• Conducted unit testing to ensure accurate and reliable outputs.
• Managed the full API development lifecycle from design to deployment.
• Deployed applications on CloudHub using CI/CD pipelines.
• Participated in requirement gathering and collaborated closely with clients and team members.
• Contributed to team meetings by providing updates on development progress and enhancements.

Project #5:GMAAP 2.0 FIELDMEDICAL

Client: AMGEN

Duration: APR 2024 – FEB 2025.

Environment: DATABRICKS

Description:

GMAAP 2.0 is a critical initiative aimed at enhancing data capabilities for the field medical system by automating the ingestion of data from salesforce into Databricks Delta Lake.The project focused on improving data integrity, standardizing KPIs, and optimizing data processes to enable accurate analytics and informed decision-making. My responsibilities included building scalable ETL pipelines, automating data workflows, and ensuring alignment with compliance and performance standards. This resulted in improved collaboration, reduced operational costs, and sustainable, data-driven growth.

Technologies Used: Python, SQL, PySpark, Databricks, Delta Lake

Key Duties and Responsibilities:

• Developed and maintained scalable PySpark scripts for data transformation as per client requirements.
• Designed and implemented complex data ingestion frameworks in Databricks using PySpark and Delta Lake.
• Built a parallel data processing framework using Databricks Workflows and APIs to improve performance and scalability.
• Managed end-to-end data flow from source systems to Delta Lake, ensuring data accuracy and consistency.
• Wrote complex SQL queries and Spark SQL using DataFrames and Datasets for advanced data transformations.
• Designed and implemented a Data Quality Automation Framework to validate data across systems.
• Coordinated with data analysts for data validation and ensured high data quality throughout the pipeline.
• Monitored and debugged Spark jobs, ensuring smooth execution of scheduled workflows.
• Led requirement gathering sessions and proposed architectural solutions aligned with business goals.
• Participated in architecture design, reviews, and technical discussions with stakeholders.
• Conducted unit testing and validation to ensure the reliability and performance of developed frameworks.
• Provided technical leadership through task allocation, resource management, and regular team updates.
• Reviewed code and offered guidance to ensure adherence to best practices and coding standards.

Project #6:AUGSST

Client: AMGEN

Duration: FEB 2025 – MAY 2025.

Environment: DATABRICKS

Description:

This project focused on building an end-to-end automated data pipeline to integrate Databricks Delta Lake with Salesforce. The goal was to streamline upstream data flow, ensuring timely and accurate data availability for business operations. The solution involved extracting and transforming data using PySpark and SQL, then seamlessly loading it into Salesforce. Automation was achieved through Databricks workflows, enabling efficient scheduling, monitoring, and data synchronization. The project improved data consistency, reduced manual intervention, and supported real-time decision-making.

Technologies Used: Python, SQL, PySpark, Databricks

Key Duties and Responsibilities:

• Took complete ownership of the end-to-end development of the data integration pipeline from Databricks Delta Lake to Salesforce.
• Designed and implemented robust ETL workflows using PySpark and SQL to extract, transform, and load data efficiently.
• Automated the entire pipeline using Databricks Workflows, ensuring reliable scheduling, monitoring, and error handling.
• Ensured high data quality, consistency, and accuracy throughout the integration process.
• Led the offshore development team by assigning tasks, reviewing code, and providing technical guidance.
• Actively collaborated with business stakeholders to gather requirements and translate them into technical solutions.
• Monitored and optimized performance of Spark jobs to ensure scalable and cost-effective processing.
• Managed deployments, version control, and CI/CD processes to ensure smooth release cycles.
• Conducted regular reviews and status meetings to track progress, address blockers, and align with project timelines.
• Delivered a fully automated and production-ready solution with minimal manual intervention and high reliability.

Project #7:GMAAP 2.0 BIOCONNECT

Client: AMGEN

Duration: MAY 2025 – PRESENT.

Environment: DATABRICKS

Description:

This project focused on enhancing data capabilities for the Bio connect system by automating the ingestion of data from PostgreSQL into Databricks Delta Lake. By improving data integrity, standardizing KPIs, and streamlining upstream data processes, the initiative aimed to support precise analytics and informed decision-making. The solution enabled seamless data flow through fully automated, scalable pipelines while ensuring compliance, improving collaboration, and reducing operational overhead. The overall impact contributed to sustainable growth and improved system performance.

Technologies Used: Python, SQL, PySpark, Databricks,Delta Lake

Key Duties and Responsibilities:

• Designed and developed end-to-end ETL pipelines to ingest data from PostgreSQL into Databricks Delta Lake using PySpark and SQL.
• Automated data extraction, transformation, and loading processes through Databricks Workflows, ensuring reliability and minimal manual intervention.
• Ensured data quality, integrity, and KPI standardization to support accurate analytics and business decision-making.
• Developed reusable and scalable PySpark scripts and complex SQL queries for transformation logic based on client specifications.
• Implemented data quality checks and monitoring frameworks to validate the flow and accuracy of data across systems.
• Collaborated with business stakeholders and data analysts to gather requirements and validate transformation logic.
• Led the offshore development team by assigning tasks, reviewing code, providing technical guidance, and ensuring delivery timelines.
• Participated in architecture design discussions and proposed optimizations aligned with compliance and performance standards.
• Conducted unit testing and validation to ensure the reliability and performance of developed frameworks.
• Provided technical leadership through task allocation, resource management, and regular team updates.
• Reviewed code and offered guidance to ensure adherence to best practices and coding standards.
• Monitored and debugged Spark jobs, ensuring smooth execution of scheduled workflows.