s
saikumar202

saikumar

@saikumar202

Azure and Palantir Data Engineer Python PySpark SQL ETL Pipelines

Índia
Inglês, Telugu
Algumas informações são exibidas no idioma inglês.
Sobre mim
I am a Data Engineer with 2.8 years of experience working with Azure and Palantir Foundry. I specialize in building scalable ETL pipelines, data ingestion workflows, and transforming large datasets using Python, PySpark, and SQL. I have experience working with Azure Data Factory, Azure Data Lake, and Databricks to design efficient data processing systems. I focus on delivering reliable and optimized data solutions for analytics and business insights.... Saiba mais

Habilidades

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saikumar202
saikumar
offline • 
Tempo médio de resposta: 2 horas

Conheça meus serviços

Engenharia de Dados
I will develop end to end etl data pipelines using python, pyspark, and azure services
A partir deUS$ 15 /projetoMais detalhes
Engenharia de Dados
I will build palantir foundry data pipelines using pyspark
A partir deUS$ 15 /projetoMais detalhes

Portfólio

Experiência profissional

Siemens

Siemens

Período integral • 2 yrs 9 mos

Palantir Data Engineer

Sep 2024 - Present • 1 yr 8 mos

Worked on data engineering solutions using Palantir Foundry to build and maintain data pipelines for analytics and operational use cases. Developed data ingestion workflows from multiple sources and implemented data transformation logic using PySpark and SQL. Built and managed datasets within Foundry and ensured proper data lineage and pipeline monitoring. Supported ontology-based data modeling and enabled data availability for dashboards and analytical applications.

Data Engineer

Jul 2023 - Aug 2024 • 1 yr 1 mo

Worked as a Data Engineer responsible for designing and developing scalable data pipelines using Python, PySpark, and SQL. Built ETL workflows to ingest data from multiple sources into Azure Data Lake using Azure Data Factory. Performed data transformation, cleaning, and validation to ensure data quality and reliability. Optimized data processing jobs and improved pipeline performance for large-scale datasets. Collaborated with analytics and business teams to deliver reliable data solutions for reporting and dashboard development.