Geetha Arunachalam

PROFESSIONAL SUMMARY
Results-driven Senior Data Engineer with over 16 years of experience delivering scalable, secure data engineering and cloud modernization solutions across healthcare, finance, and public sector environments. Specialized in:

• Building cloud-native data pipelines using Azure Databricks, Azure Data Factory, Synapse Analytics, Delta Lake, ADLS Gen2, as well as AWS Glue (PySpark), Redshift, Athena, S3, and Lake Formation.
• Leading end-to-end migrations from legacy platforms like Cloudera/Hive to Delta Lake on Azure and Redshift/Iceberg on AWS for modern analytics and machine learning workloads.
• Designing and implementing robust ETL/ELT architectures using PySpark and Python on Azure Databricks and AWS Glue, incorporating dynamic partitioning, Z-Ordering, and performance tuning strategies.
• Expertise in big data transformations, schema modeling, and data governance using Azure Purview and AWS Glue Data Catalog, with CI/CD automation via Azure DevOps, AWS Code Pipeline, and Terraform.

Widely recognized for strong problem-solving abilities, cross-functional leadership, and the ability to translate complex data challenges into actionable analytics solutions aligned with business and product goals.

PROFESSIONAL SUMMARY
Results-driven Senior Data Engineer with over 16 years of experience delivering scalable, secure data engineering and cloud modernization solutions across healthcare, finance, and public sector environments. Specialized in:

• Building cloud-native data pipelines using Azure Databricks, Azure Data Factory, Synapse Analytics, Delta Lake, ADLS Gen2, as well as AWS Glue (PySpark), Redshift, Athena, S3, and Lake Formation.
• Leading end-to-end migrations from legacy platforms like Cloudera/Hive to Delta Lake on Azure and Redshift/Iceberg on AWS for modern analytics and machine learning workloads.
• Designing and implementing robust ETL/ELT architectures using PySpark and Python on Azure Databricks and AWS Glue, incorporating dynamic partitioning, Z-Ordering, and performance tuning strategies.
• Expertise in big data transformations, schema modeling, and data governance using Azure Purview and AWS Glue Data Catalog, with CI/CD automation via Azure DevOps, AWS Code Pipeline, and Terraform.

Widely recognized for strong problem-solving abilities, cross-functional leadership, and the ability to translate complex data challenges into actionable analytics solutions aligned with business and product goals.

CERTIFICATIONS

• 🟢 AWS Certified Database – Specialty – Amazon Web Services (Feb 2023)
• 🟢 Advanced Certification in Data Science and AI – IIT Madras / Intellipaat (2022)
• Bachelor of Computer science