I'm Tiruni Karunarathna, a data engineer specializing in Data Pipelines and Analytics Infrastructure

What People Say

★★★★★

"Tiruni's data pipelines transformed our analytics. ETL is now 3x faster!"

SR
Sarah Rodriguez
VP of Engineering
★★★★★

"The warehouse migration was seamless. Architecture is elegant and efficient."

MJ
Michael Johnson
Data Director
★★★★★

"Real-time streaming handling millions of events daily. Robust and documented!"

EP
Emily Patterson
CTO, DataStream
★★★★★

"Future-proof analytics platform. Exceptional code quality and documentation."

DL
David Lee
Lead Architect
★★★★★

"ML pipeline infrastructure is now our AI backbone. Outstanding performance!"

AC
Amanda Chen
Head of AI

Selected Works

Real-Time Data Pipeline

Built a scalable ETL pipeline processing millions of events daily using Apache Kafka and Spark, reducing data latency by 70%.

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Data Warehouse Migration

Architected and executed migration from on-premise to cloud data warehouse, optimizing query performance and reducing costs by 40%.

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ML Data Infrastructure

Designed feature store and data versioning system supporting ML models in production, enabling faster model deployment cycles.

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Interactive Tableau Dashboards

Created comprehensive business intelligence dashboards in Tableau, providing real-time insights and enabling data-driven decision making across departments.

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About Tiruni Karunarathna

I'm a data engineer passionate about building robust data infrastructure and pipelines that transform raw data into actionable insights. With expertise in distributed systems and cloud technologies, I help organizations scale their data operations.

My approach combines strong technical skills, problem-solving abilities, and a focus on building reliable, efficient data solutions that drive business value.

Python Apache Spark SQL ETL/ELT AWS Airflow Kafka Data Modeling
def process_data():
SELECT * FROM analytics
spark.read.parquet()
pipeline.transform()
3+
Years Experience
45+
Projects Completed
10TB+
Data Processed
99.9%
Pipeline Uptime

Let's Work Together

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