ARIVUMANI RAMALINGAM

• Architected, Designed, and Deployed Data Pipeline Frameworks
  Built and deployed scalable data pipeline frameworks in Azure Kubernetes for moving polyglot data payloads to the Data Lakehouse. Actively utilized in production by all data vertical teams, these pipelines streamline data workflows across GEICO zones. Trained and mentored over 100 developers to adopt and leverage these services effectively.
• Developed Data Pipelines for Analytical and Data Science Consumption
  Designed and implemented pipelines for transferring polyglot data payloads to ADLS and Snowflake, supporting analytics and data science initiatives. Leveraged tools such as Apache Flink, Airbyte, Spark, Azure Data Factory, Azure Databricks, and DBT. Proficient in Java, Python, Spark, Scala, DBT, SQL, and PL/SQL.
• Integrated with Data Lakehouse
  Enabled seamless data storage in RAW and Conformed zones of the Data Lakehouse using technologies like Apache Iceberg, Polaris REST Catalog, ADLS Gen2, Hive, Spark, Snowflake, Hudi, Blaze, DBT, Ranger, and related tools.
• Implemented Data Quality and Balance Control Framework
  Designed an end-to-end framework ensuring data quality and accuracy. Utilized SQL Server PL/SQL, control data frameworks, Guarantee Delivery API frameworks, DBT SQL engines, and Power BI to monitor and validate data integrity.
• Automated Deployment Workflows
  Developed deployment automation pipelines using Airflow, Azure DevOps (ADO), and Python libraries, leveraging REST API capabilities for various ingestion tools.
• Deployed Scalable Solutions in Azure Kubernetes
  Deployed microservices-based operators, executors, and ingestion frameworks in Azure Kubernetes. Focused on system stability, optimized resource utilization, scaling, and implementing business continuity and disaster recovery measures.

Technologies - Apache Flink, Airbyte, Spark, Azure Data Factory, Azure Databricks, and DBT. Java, Python, Spark, Scala, DBT, SQL, and PL/SQL, Apache Iceberg, Polaris REST Catalog, ADLS Gen2, Hive, Spark, Snowflake,, DBT, Ranger, Airflow, Azure DevOps (ADO), Azure Kubernetes, Helm, Shell Scripting, Dev, Kyuubi, Blaise

Adopted and Implemented Licensed PaaS Data Ingestion Tools ( 2020 - 2022 )
Developed, customized, and implemented licensed PaaS ingestion tools such as Fivetran, HVR, and Confluent Kafka to seamlessly move data from diverse sources to ADLS Gen2 and Snowflake. Collaborated closely with vendors to align these tools with GEICO's security standards and compliance requirements.

Tools and Technologies - Fivetran, HVR, Confluent Kafka, ADLS Gen2, Snowflake, DBT, Azure DevOps, Java, Python, Scala, Spark, SQL/PLSQL, Databricks, Azure Data Factory, SQL Server, Oracle, Flat Files, and Message Hubs

Architected and Implemented Kafka Connect-Based Ingestion Architecture ( 2018 - 2020 )
Designed and developed a Kafka Connect-based ingestion framework to build robust data pipelines. Collaborated closely with Confluent, Microsoft, and Pivotal developers to enhance pipeline capabilities and ensure seamless integration with enterprise systems

Tools and Technologies - Kafka Connect, Open Source Kafka, Debezium, JDBC Connectors, ADLS Gen2 Sink, Snowflake Sink, DBT, Databricks, Spark, Java, Python, Scala, Jenkins, Git

Architected and Implemented Big Data Pipelines Using Open-Source Frameworks ( 2015 - 2017 )
Designed, developed, and implemented scalable big data pipelines leveraging open-source ingestion platforms. Utilized technologies such as Spring Boot, Spring Cloud Dataflow, Kubernetes, Apache Kafka, Hive, Hadoop, HBase, Camus Framework, Spark, MapReduce, and Jenkins to streamline data processing and integration

Tools and Technologies - Spring Boot, Spring Frameworks, Java, Spring Cloud Dataflow, Kubernetes, Apache Kafka, Hive, Hadoop, HBase, Camus Framework, Spark, MapReduce, Jenkins

Enhanced Auto Insurance Coverage Handling for GEICO Online Portal ( 2013 - 2014 )
Developed and maintained functionality to manage auto insurance coverages based on user requests. Utilized Blaze Rules Engine to implement decision-making logic, ensuring accurate and efficient processing of coverage options

Technologies - Java, Spring, JSF, Spring MVC, Blaze, Jenkins, DB2, Oracle, SQL Server, Sonar

Led Java-Based System Development for Health Insurance Coverage Management
Designed and Developed a Java-based system to manage health insurance coverages for members and agents. Designed and contributed to the creation of a Common Sales Tool, enabling adoption and utilization across multiple health insurance providers

Technologies - Java, J2EE, Struts, Spring, JSP, JavaScript, Ajax, JQuery, SQL/PLSQL, DB2, JRules, Jenkins

Designed and developed an Unemployment Insurance application portal for the State of Minnesota to streamline the processing of unemployment claims. Collaborated closely with the business team to gather requirements and build a Java-based system to collect, process, and deliver unemployment benefits to Minnesota applicants

Technologies - Java, Struts, JSP, JavaScripts, MySQL

Developed and implemented a data extraction process for water quality XML files, enabling seamless integration with MQ to support critical subsystems such as the Immunization Registry (ImmPact), Laboratory Information Tracking System (LITS+), and Laboratory Management System (StarLIMS), improving data accessibility and workflow efficiency

Technologies - Java, Oracle, XML, SQL, PL/SQL, MQ Series,

• Orchestrated development of Rentalnet truck leasing application
• Streamlined reservation, contract, and payment processes
• Enhanced system efficiency through Big Data engineering

Technologies - Java, J2EE, JavaScript, Struts, JSP