Abhijna P S

I am a Data Engineer with 2.8 years of experience building scalable ELT/ETL pipelines and data platforms for analytics and reporting. I specialize in designing end-to-end workflows using Python, PySpark, SQL, Airflow, Airbyte and AWS services to process large datasets reliably.

I have automated client onboarding, data ingestion, and deployment processes to dramatically reduce manual effort and improve consistency—cutting onboarding time by 80% at my current employer. I build API-driven data services and serverless microservices with FastAPI, Flask, Lambda and API Gateway to expose datasets securely for downstream consumers.

My work includes optimizing Amazon Redshift warehouses with materialized views and mapping logic that improved cross-platform data consistency and prevented null-driven data loss. I also implement data governance controls such as masking and access policies to protect sensitive analytics data.

I deliver production-grade pipelines with CI/CD, Docker, Git and monitoring (CloudWatch), and have built projects in streaming (Kafka → Snowflake) and ML-enabled tooling (RAG + local LLMs) to extend data capabilities. I am motivated to join teams that value reliable data foundations and scalable analytics solutions.