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geethu sree

@geethusree

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AWS Data Engineer at IBM client who built Matillion flows and Power BI reporting for Merck’s COGS data.

India

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At IBM client, I designed Matillion ETL flows for Merck’s COGS work, transforming External Contract Data with business logic to calculate costs across a 10-year time horizon. I also built Power BI dashboards and Inforiver Matrix reporting pages that let business users view and modify calculated cost data.

Across my data engineering work, I built AWS pipelines for data ingestion, transformation, and analytics using services including Glue, Redshift, and S3. At Cognizant, I designed cloud-native contact center solutions with Amazon Connect, Lambda, and Lex; at Silicon Techlabs, I processed JSON data into Parquet for querying with Athena.

Experience

Work history, roles, and key accomplishments

Data Engineer

IBM

May 2025 - Aug 2026 (1 year 3 months)

Analyzed and validated client source data for a multi-stage AWS-based data pipeline, ensuring cross-referential data integrity. Designed and built Matillion ETL flows for data extraction and transformation, and developed Power BI dashboards for cost data visualization.

AWS Matillion ETL Power BI Inforiver Matrix SQL Data Migration Data Mapping DDL Confluence

AWS Data Engineer

IBM

Jan 2025 - Apr 2025 (3 months)

Built and maintained data pipelines ingesting data from SAP and Salesforce into Amazon Redshift. Authored DDLs, created Redshift views, and developed AWS Managed Apache Airflow DAGs to automate data workflows.

AWS Amazon Redshift Airflow DDL Data Pipelines SAP Salesforce SQL

Programmer Analyst (AWS Developer)

Cognizant

Nov 2022 - Oct 2024 (1 year 11 months)

Designed and deployed cloud-native contact center solutions using Amazon Connect, integrating Lambda, Lex, and Alexa. Built serverless, event-driven backend integrations using AWS Lambda, SQS, and DynamoDB.

AWS Amazon Connect Lambda Lexis Alexa Amazon SQS DynamoDB Serverless Event Driven Architecture

Data Engineer

Silicon Techlabs

Aug 2020 - Aug 2022 (2 years)

Built an AWS-based data ingestion solution for daily batch transactions, forming an early data lake pipeline on S3. Developed AWS Glue jobs in Python and used Apache Spark to convert JSON to Parquet for optimized querying via Athena.