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Teeja SenthilKumar

Data Engineer | Python · SQL· Apache Airflow ·AWS · PySpark | ETL/ELT · BigQuery · Snowflake · dbt | LLM · RAG Pipelines · LangChain | 1 Year Production Experience

Greater Hyderabad Area

< 1 year of work experience

Lognormal Analytics
Nov 20256 mosApr 2026

Hyderabad, Telangana, India

• Built and orchestrated Apache Airflow DAGs from scratch for an iGaming analytics platform serving clients across the UK and Turkey writing and contributing to pipelines that managed upstream and downstream data dependencies for pre-match and live betting KPI feeds. • Designed and implemented ETL pipelines using Python, Polars, and Pandas to ingest, aggregate, and transform raw client data into structured analytics-ready datasets powering KPI dashboards consumed by international iGaming clients via the Falcon.io platform. • Set up and managed multi-database storage infrastructure from scratch dumping and persisting processed data across MongoDB and PostgreSQL, handling schema design, storage processes, and data consistency across both relational and document stores. • Worked across the full data stack on AWS querying and processing data using Amazon S3 and Amazon Athena, and extended cloud data work to Google BigQuery for cross-platform analytics delivery. • Built end-to-end data artifacts and reporting views including new HTML artifact creation and front-end integration backed by a Node.js API layer and hosted file services, delivering complete client-facing dashboards from raw data ingestion to final display.
Cubeaisolutions Tech Pvt Ltd
May 20256 mosOct 2025

Bengaluru, Karnataka, India

• Built RAG pipelines using LangChain and FAISS vector databases to process and semantically search over research papers and documents implementing embedding generation, chunking strategies, and retrieval logic for LLM-powered summarization workflows. • Developed document intelligence features including embedding pipelines and automated summarization using LLM APIs enabling end-to-end ingestion, semantic indexing, and structured output generation from unstructured research content. • Worked on computer vision projects building and testing deep learning models applying vision pipelines to real-world tasks alongside LLM development work within the same product delivery cycle. • Prepared and processed training datasets for both NLP and vision models handling data cleaning, annotation pipelines, and feature engineering to support model development and evaluation workflows.

Teeja’s AI Stack

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grok
grok
langfuse
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Education

Amrita Vishwa Vidyapeetham

Master of Science - MS, Data Scientist

Amrita Vishwa Vidyapeetham

20215 yrs2026
Amrita Vishwa Vidyapeetham

HSC, CBSE

Amrita Vishwa Vidyapeetham

20192 yrs2021

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Headline

Data Engineer | Python · SQL· Apache Airflow ·AWS · PySpark | ETL/ELT · BigQuery · Snowflake · dbt | LLM · RAG Pipelines · LangChain | 1 Year Production Experience

About

Data and Analytics Engineer with 1 year of experience designing and deploying end-to-end ETL/ELT pipelines, orchestrating workflows, and delivering cloud data solutions across multiple platforms. Proven ability to work across the full data stack from raw ingestion and real-time streaming to data modelling and analytical reporting.

Location

Greater Hyderabad Area

AI stack

antigravity

grok

langfuse

notebooklm

Work experience

Data Engineer at Lognormal Analytics, Nov 2025 - Apr 2026 · 6 mos, Hyderabad, Telangana, India, • Built and orchestrated Apache Airflow DAGs from scratch for an iGaming analytics platform serving clients across the UK and Turkey writing and contributing to pipelines that managed upstream and downstream data dependencies for pre-match and live betting KPI feeds. • Designed and implemented ETL pipelines using Python, Polars, and Pandas to ingest, aggregate, and transform raw client data into structured analytics-ready datasets powering KPI dashboards consumed by international iGaming clients via the Falcon.io platform. • Set up and managed multi-database storage infrastructure from scratch dumping and persisting processed data across MongoDB and PostgreSQL, handling schema design, storage processes, and data consistency across both relational and document stores. • Worked across the full data stack on AWS querying and processing data using Amazon S3 and Amazon Athena, and extended cloud data work to Google BigQuery for cross-platform analytics delivery. • Built end-to-end data artifacts and reporting views including new HTML artifact creation and front-end integration backed by a Node.js API layer and hosted file services, delivering complete client-facing dashboards from raw data ingestion to final display.

AI/ ML Engineer at Cubeaisolutions Tech Pvt Ltd, May 2025 - Oct 2025 · 6 mos, Bengaluru, Karnataka, India, • Built RAG pipelines using LangChain and FAISS vector databases to process and semantically search over research papers and documents implementing embedding generation, chunking strategies, and retrieval logic for LLM-powered summarization workflows. • Developed document intelligence features including embedding pipelines and automated summarization using LLM APIs enabling end-to-end ingestion, semantic indexing, and structured output generation from unstructured research content. • Worked on computer vision projects building and testing deep learning models applying vision pipelines to real-world tasks alongside LLM development work within the same product delivery cycle. • Prepared and processed training datasets for both NLP and vision models handling data cleaning, annotation pipelines, and feature engineering to support model development and evaluation workflows.

Education

Master of Science - MS, Data Scientist, Amrita Vishwa Vidyapeetham

HSC, CBSE, Amrita Vishwa Vidyapeetham