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Data Engineer with 5+ years of experience designing scalable data platforms and supporting AI/ML-driven applications. Skilled in building robust ETL/ELT pipelines, real-time streaming systems, and cloud-native architectures using Spark, Kafka, and Airflow. Proven ability to enable end-to-end machine learning workflows from ingestion and feature engineering to deployment and monitoring. Delivered secure, high-performance data solutions in regulated environments, including HIPAA-compliant systems. Experienced in LLM applications using Hugging Face and RAG pipelines, along with data governance, validation, and orchestration to ensure reliability and quality across batch and streaming workloads.…Data Engineer with 5+ years of experience designing scalable data platforms and supporting AI/ML-driven applications. Skilled in building robust ETL/ELT pipelines, real-time streaming systems, and cloud-native architectures using Spark, Kafka, and Airflow. Proven ability to enable end-to-end machine learning workflows from ingestion and feature engineering to deployment and monitoring. Delivered secure, high-performance data solutions in regulated environments, including HIPAA-compliant systems. Experienced in LLM applications using Hugging Face and RAG pipelines, along with data governance, validation, and orchestration to ensure reliability and quality across batch and streaming workloads.

Amogh D

Data Engineer, Software Engineer, AI Engineer, +4

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Data Engineer with 5+ years of experience designing scalable data platforms and supporting AI/ML-driven applications. Skilled in building robust ETL/ELT pipelines, real-time streaming systems, and cloud-native architectures using Spark, Kafka, and Airflow. Proven ability to enable end-to-end machine learning workflows from ingestion and feature engineering to deployment and monitoring. Delivered secure, high-performance data solutions in regulated environments, including HIPAA-compliant systems. Experienced in LLM applications using Hugging Face and RAG pipelines, along with data governance, validation, and orchestration to ensure reliability and quality across batch and streaming workloads.…Data Engineer with 5+ years of experience designing scalable data platforms and supporting AI/ML-driven applications. Skilled in building robust ETL/ELT pipelines, real-time streaming systems, and cloud-native architectures using Spark, Kafka, and Airflow. Proven ability to enable end-to-end machine learning workflows from ingestion and feature engineering to deployment and monitoring. Delivered secure, high-performance data solutions in regulated environments, including HIPAA-compliant systems. Experienced in LLM applications using Hugging Face and RAG pipelines, along with data governance, validation, and orchestration to ensure reliability and quality across batch and streaming workloads.

Available to hire

Data Engineer with 5+ years of experience designing scalable data platforms and supporting AI/ML-driven applications. Skilled in building robust ETL/ELT pipelines, real-time streaming systems, and cloud-native architectures using Spark, Kafka, and Airflow. Proven ability to enable end-to-end machine learning workflows from ingestion and feature engineering to deployment and monitoring.

Delivered secure, high-performance data solutions in regulated environments, including HIPAA-compliant systems. Experienced in LLM applications using Hugging Face and RAG pipelines, along with data governance, validation, and orchestration to ensure reliability and quality across batch and streaming workloads.

Skills

Experience Level

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Work Experience

AI Platform Engineer / Data Engineer at Honeywell USA

August 1, 2022 - Present

Designed and supported end-to-end AI/ML platforms on AWS, improving platform efficiency by 40%. Built and managed ML pipelines using MLflow, Kubeflow, and SageMaker, improving experiment tracking, model versioning, and deployment efficiency by nearly 50%. Developed LLM-based applications using Hugging Face and RAG pipelines to enable semantic search and intelligent retrieval, improving relevance by 35%. Created and maintained data pipelines supporting ML workflows using PySpark, Kafka, and Airflow. Implemented monitoring and validation for ML models to enable timely retraining. Designed ETL/ELT workflows using SQL, dbt, and Informatica to reduce manual data handling by nearly 45%. Developed data lake and warehouse solutions on AWS (S3, Redshift, Glue) and collaborated with data science and product teams to deliver AI-driven solutions, improving delivery timelines by 30%.

Data Engineer at Mindtree India

January 1, 2019 - December 1, 2020

Built and maintained scalable batch and real-time data pipelines using PySpark, Kafka, and Airflow, improving processing speed by about 35% and enabling faster reporting. Implemented Delta Lake-based medallion architecture (Bronze/Silver/Gold) to organize raw and curated data layers, improving data quality and usability. Developed REST APIs using FastAPI and Flask to serve ML models and data services. Containerized services using Docker and Kubernetes to improve deployment consistency and reduce environment-related issues by 40%. Optimized query performance across Snowflake, Redshift, and BigQuery, reducing execution time by 40–50%. Built streaming pipelines using Kafka and event-driven architecture to enable near real-time processing. Applied data quality validation using Great Expectations, reducing inconsistencies by about 30%. Collaborated with analytics and business teams to deliver clean datasets for faster, more accurate decision-making.