Collaborated with Finance Internal Audit to define and track data quality KPIs (freshness, precision, completeness). Built data pipelines using DataSwarm, Python, and Spark to migrate and transform financial data from Oracle EBS to Fusion (via BICC/BIP) into Hive, MySQL, and Presto. Delivered reporting solutions in Tableau, Incorta, and Unidash. Supported on-call issue resolution, table ownership, and pipeline reliability, Implemented KPI metrics for Finance business users using Tableau, Incorta and Unidash.

Led end-to-end cloud migration of airline passenger data (~300 datasets) from on-prem to AWS (Athena, S3, DynamoDB). Designed identity and access solutions using Amazon Cognito with federated SSO. Built and deployed serverless data pipelines using Lambda, Glue, Step Functions, and Docker to integrate operational systems (PAXUS, MMA). Delivered 2,000+ KPI metrics for 35 airline clients using Spark, Python, and AWS-native tools.

Multiple Client Engagements (Telecom, Mining, Aviation, Healthcare)

Delivered enterprise-scale Big Data, Analytics, and Data Engineering solutions across AWS and Azure platforms. Led the design and development of data lakes, ETL/ELT pipelines, and analytics platforms for clients in aviation, telecom, mining, and healthcare.

Aviation (AWS): Architected secure, automated data platform with monitoring, logging, and large-scale ingestion for inflight entertainment systems.

Mining (AWS): Built ELT pipelines for 6 mining sites; implemented 1,200+ KPIs and automated Oracle/SQL ingestion using Step Functions and Sqoop.

Telecom (Hadoop/Spark): Migrated 50+ TB of Teradata data; designed Hive data models, Spark SQL pipelines, and optimized analytics for AT&T.

Healthcare (AWS): Integrated 10TB+ of encrypted claims data into DynamoDB; developed Tableau dashboards for contract performance visibility.

Tech Stack: AWS (Glue, EMR, Lambda, S3), Azure (Data Factory, U-SQL), Spark, Hive, Sqoop, MySQL, Python, Bash, Tableau, Power BI, Teradata, ERWIN.

Engineered an AWS-based data platform to integrate and transform operational and financial data from six mining sites. Developed scalable data pipelines using PySpark, Spark SQL, and AWS services (EMR, Lambda, Step Functions, Glue). Automated ingestion from Oracle, SQL Server, and JIGSAW using Sqoop and serverless workflows. Delivered 1,200+ site-level KPIs and migrated legacy Azure Data Factory pipelines (U-SQL) to AWS, ensuring high-performance, production-ready data flows.

Technical -AWS- EMR, EC2, Lambda, Step functions, CloudWatch, S3, Spark, Python, Genie, Athena, AWS

Glue. MS AZURE -USQL, AZURE Data Factory, SQL Server 2016, Hadoop, HDFS, HIVE, SQOOP, ORACLE

Built large-scale data lakes and pipelines for global clients across telecom, mining, healthcare, and e-commerce sectors. Led Teradata-to-Hadoop migrations and Spark-based modeling platforms for AT&T. Engineered Azure Data Lake and U-SQL pipelines for Barrick Gold’s operational and financial reporting. Designed AWS DynamoDB-based claims integration for Opko Health, and built marketing analytics pipelines for StubHub. Delivered insights through dashboards in Tableau and Power BI. Technologies included Hadoop, Spark, Hive, Azure Data Factory, AWS Glue, and SQL-based ETL tools.