Likith B

• Provided hands-on production support for enterprise data warehouse systems, troubleshooting job failures, data issues, and performance bottlenecks to meet strict SLA requirements. • Developed and maintained Unix shell scripts to automate ETL job execution, file transfers, logging, monitoring, and recovery processes across multiple environments. • Worked extensively with IBM DB2, writing and optimizing complex SQL queries, views, and stored procedures for data extraction, validation, and reconciliation. • Performed root cause analysis for production incidents, identifying upstream/downstream impacts and implementing permanent fixes to prevent recurrence. • Monitored daily batch and intraday data loads, proactively identifying data quality issues and coordinating resolutions with application, infrastructure, and database teams. • Utilized Google Cloud BigQuery Console to validate ETL outputs, perform data reconciliations, and support ad-hoc analytical queries. • Tuned SQL performance by analyzing execution plans, indexing strategies, and query optimization techniques for large-scale datasets. • Supported on-call rotations, handling high-priority incidents, data delays, and operational issues in a fast- paced, business-critical environment.

• Expert in Unix/Linux shell scripting, automating data ingestion, validation, and job orchestration to reduce manual intervention and meet stringent healthcare SLAs and compliance requirements (e.g., HIPAA). • Advanced proficiency with SQL and IBM DB2, crafting complex queries, stored procedures, and performance tuning optimized for processing sensitive healthcare datasets. • Designed and implemented enterprise-level data warehouses supporting finance, HR, and operations analytics. • Migrated on-prem data marts to BigQuery using BQ Console and Data Transfer Service. • Designed and executed complex SQL queries using GCP BQ Console to analyze petabyte-scale datasets. • Defined KPIs and business metrics within the data warehouse layer for consistency. • Built reusable Talend Jobs for data extraction, transformation, and loading across multiple domains. • Implemented Infrastructure as Code and DevOps practices using Terraform and Cloud Build pipelines, with Git-based version control, to enforce repeatable, compliant deployments across development, testing, and production environments. • Developed custom routines in Java within Talend for advanced data processing and error handling. • Used BigQuery Console to validate and monitor daily ETL load performance and storage usage.

• Developed Spark streaming model, which gets transactional data as input from multiple sources, and create multiple batches and later processed for already trained fraud detection model and error records. • Extensive knowledge in Data transformations, Mapping, Cleansing, Monitoring, Debugging, performance tuning and troubleshooting Hadoop clusters. • Involved in converting Hive/SQL queries into Spark transformations using Spark RDDs, Python and Scala. • Developed DDLs and DMLs scripts in SQL and HQL for creating tables and analyze the data in RDBMS and Hive. • Used Sqoop to import and export data from HDFS to RDBMS and vice-versa. • Created Hive tables and involved in data loading and writing Hive UDFs. • Exported the analyzed data to the relational database MySQL using Sqoop for visualization and to generate reports. • Loaded the flat files data using Informatica to the staging area. • Researched and recommended suitable technology stack for Hadoop migration considering current enterprise architecture.