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KarthikMahalingam8881/README.md

💫 About Me:

Software & Data Engineer working at the intersection of engineering and customer-facing systems. My experience includes L1/L2-style SaaS support: triaging issues, debugging APIs and data workflows, validating data with SQL, collaborating with engineering on root-cause analysis, and documenting fixes to reduce repeat incidents.

I build scalable backend systems, data pipelines, and automation workflows using Python, SQL, and AWS, with a strong focus on reliability, observability, and production readiness.

🛠 Support & Troubleshooting Experience:

• Investigated and resolved production issues including API failures, schema drift, data inconsistencies, and batch orchestration errors.

• Used SQL and logs to validate data correctness and identify root causes.

• Worked closely with engineering teams to distinguish configuration issues from true product defects.

• Documented fixes and process improvements to reduce repeat incidents.

🌐 Socials:

LinkedIn email

💻 Tech Stack:

AWS Python MySQL Postgres Apache Airflow Docker Pandas Snowflake GitHub Actions Apache Spark C++ Java Bash Script Google Cloud

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  1. Amazon-Fake-Review-Detection-Pipeline Amazon-Fake-Review-Detection-Pipeline Public

    Amazon Fake Review Detection Pipeline

    Python 1

  2. Redshift-Analytics-Pipeline Redshift-Analytics-Pipeline Public

    Forked from san089/Udacity-Data-Engineering-Projects

    A scalable AWS Redshift data warehouse project that loads user activity and song data from S3, stages it, and transforms it into a star schema for analytical queries like “What songs were played th…

    Python

  3. Optimizing-Credit-Card-Fraud-Detection Optimizing-Credit-Card-Fraud-Detection Public

    This project converts a Jupyter-based machine learning model into a modular, cloud-ready data engineering pipeline using Python, AWS S3, and PostgreSQL. It enables automated data ingestion, transfo…

    Jupyter Notebook