Open to opportunities

naman goel

@namangoel

Message

Senior Data Engineer specializing in cloud-native ETL/ELT and lakehouse platforms for AI-ready analytics.

India

Message

What I'm looking for

I’m looking to build cloud-native, governed data platforms that power analytics and AI—especially real-time streaming and lakehouse systems—where I can own ETL/ELT performance, data quality frameworks, and end-to-end orchestration.

I’m a Senior Data Engineer with 4+ years of experience designing, building, and optimizing large-scale distributed data platforms across healthcare, pharmaceutical, and marketing analytics.

I develop high-performance ETL/ELT pipelines using PySpark, SQL, Databricks, AWS, Snowflake, and Apache Airflow—processing terabytes of enterprise data with a strong focus on Spark performance optimization and reliable, governed storage.

My work centers on Lakehouse architecture and data quality: I’ve implemented Delta Lake bronze/silver/gold layers with ACID transactions and time-travel, and deployed Great Expectations frameworks to catch schema drift and anomalies early.

I’m also building toward real-time streaming and AI-powered data platforms, including Generative AI prototypes (OpenAI, Hugging Face) and LangChain RAG pipelines integrated into enterprise data lakes to reduce analyst turnaround time.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Dozee

Jan 2026 - Present (6 months)

Contributing to a centralized cloud-native Data Management System for physiological health signals using AWS, Databricks, and Apache Spark. Assisting with scalable ingestion pipelines and working with teams to standardize data ingestion, storage, and governance within a Lakehouse platform.

AWS Databricks Apache Spark Lakehouse Architecture Data Ingestion Data Governance Data Management Systems

Senior Associate

Axtria Ingenious Insights

Jan 2022 - Jan 2026 (4 years)

Designed and optimized distributed PySpark ingestion pipelines for multi-terabyte datasets across multiple enterprise data sources. Built production orchestration with Airflow and Tidal, implemented Delta Lake Lakehouse layers, deployed Great Expectations for data quality, and created LangChain RAG prototypes; also supported migrations to AWS and Snowflake for multiple clients.