Open to opportunities

Amisha Tripathy

@amishatripathy

Senior Data Engineer with 4+ years building scalable cloud-native data platforms for reliable batch and streaming analytics.

India

Message

What I'm looking for

I’m looking for a role where I can own and modernize cloud data platforms—building high-throughput batch/stream pipelines, metadata-driven governance, and observability—so teams deliver reliable data products with less operational overhead.

I’m a Senior Data Engineer with 4+ years architecting, building, and scaling cloud-native data platforms, distributed processing systems, and analytics infrastructure for enterprise-scale workloads. I specialize in designing high-throughput batch and streaming architectures, metadata-driven platforms, self-service analytics ecosystems, and production-grade data products that support millions of records.

At Schlumberger, I’ve built metadata-driven ETL/ELT frameworks, scalable lakehouse architectures, and medallion (Bronze/Silver/Gold) patterns to deliver governed, analytics-ready datasets. I also lead platform modernization by optimizing SQL and Spark workloads (up to 65% performance gains), automating validation and observability, and reducing manual operational effort by more than 90% through workflow automation—while serving as technical owner and mentoring engineers with a reliability-first mindset.

Experience

Work history, roles, and key accomplishments

Software Engineering Intern

Microsoft

Jan 2021 - Present (5 years 5 months)

Built and shipped a production-grade collaboration platform using React and Firebase, implementing scalable authentication and real-time multi-user workflows. Designed backend data models and APIs for collaborative product features and deployed/operated the application on cloud infrastructure.

React Firebase Authentication API Development Data Modeling Data Integrity cloud deployment

Data & ML Engineering Intern

High Radius

Jan 2021 - Present (5 years 5 months)

Built an end-to-end machine learning pipeline to predict invoice payment behavior using Scikit-learn, covering data ingestion, feature engineering, model training, and inference. Deployed the model in a full-stack application and worked with real-world financial datasets to address data quality, bias, and feedback loop considerations.

Machine Learning scikit learn Feature Engineering Model Training Data Ingestion Data Quality Financial Analytics