Ratnakkar M
Senior Data Manager @Baxter International Inc.
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WORK HISTORY
Senior Data Manager @Baxter International Inc.
Amherst, NY, US
As a Data Manager at Baxter International, I managed and collaborated with multiple cross-functional teams, including RCM and logistics teams, to design and evolve scalable data platforms on Google Cloud. I leveraged Dataproc (Spark), Dataflow, and BigQuery to deliver reliable batch and streaming pipelines, while guiding teams on core GCP services such as Cloud Storage, Pub/Sub, Cloud Functions, Cloud Run, and API Gateway. I supported orchestration and observability using Cloud Composer (Airflow), Cloud Logging, and Cloud Monitoring, and played a key role in data migrations and serverless architectures. In addition, I partnered closely with business and analytics teams using Looker/Looker Studio, Tableau, and Power BI, along with transformation tools like Dataform/dbt and Cloud Data Fusion, to enable high-quality reporting and actionable insights across CVS Health.
ABOUT RATNAKKAR M
Experienced data management professional with over two decades of expertise in SQL development, data modeling, data governance, and large-scale data engineering. Strong background in designing, optimizing, and managing end-to-end data platforms across AWS and Google Cloud Platform (GCP). Highly skilled in building and maintaining complex batch and streaming pipelines using Spark, Hadoop, Dataproc, Dataflow, and cloud-native services such as AWS EMR, Glue, S3, Lambda, BigQuery, Pub/Sub, and Cloud Storage. Proven ability to implement robust data management frameworks, including data quality, metadata management, lineage, security, and compliance, ensuring accuracy, performance, and reliability of enterprise data assets. Demonstrated success in driving business insights, improving operational efficiency, and delivering scalable data solutions across industries. Well-versed in Agile methodologies, CI/CD automation, and AI/ML-enabled data workflows. Currently serving in a senior data leadership role, leading the design and deployment of resilient, cloud-native data processing infrastructures across AWS and GCP environments.
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