shanmukeswar karrothu

I’m a Data Engineer with around 3 years of experience building and supporting data platforms, ETL pipelines, data warehouses, and analytics solutions, primarily in the healthcare and commercial analytics domain. My core strengths are SQL, PL/pgSQL, Python, PySpark, AWS and data warehousing, with hands-on experience working with Amazon Redshift, S3, Glue, Athena and Aurora.

In my current role at TCS, I work on a global Commercial Sales Analytics Platform built on Amazon Redshift. I work with large-scale fact and dimension models, SQL stored procedures, ETL transformations, data quality and reconciliation, and datasets consumed by reporting and engineering teams across multiple markets. I have worked in solving complex data issues where business rules, historical data and multiple source systems need to be reconciled.

Previously, I worked on an enterprise data warehouse modernization project involving migration from Oracle to Amazon Redshift. I developed PL/pgSQL procedures and incremental ETL processes using dimensional modeling and SCD Type 2 concepts, and worked with AWS services including S3, Glue and Redshift. I also contributed to performance improvements, UAT, production support, root-cause analysis and data validation using SQL and Python.

I particularly enjoy solving data quality and pipeline problems rather than simply moving data from one system to another. For example, I have investigated production KPI anomalies, traced them through source and transformation logic, identified duplicate or incorrect business keys, and worked with teams to resolve the underlying issue.

I’m currently interested in growing further as a modern Data Engineer, particularly in Databricks, PySpark, cloud data platforms, and scalable data pipelines. I’m also interested in how AI can be applied to data engineering and analytics workflows.

I’m most interested in Data Engineer, Analytics Engineer, Data Warehouse Engineer and related roles where I can combine strong SQL/data warehousing fundamentals with modern cloud and distributed data technologies. I’m especially interested in product companies, healthcare/pharma, analytics, and data-driven organizations where data quality and engineering have a meaningful business impact.