A True Data Sciencist Architect to setup my all types of Data Automation projects using Python & PowerBI

We are looking a Data Sciencist Architect who can do below for us.

Design Data Warehousing System

Develope ETL using python scripts/C# project or any other tool and setup those on server or some other service to run every on a particular time to fetch data from multiple sources and dump it in to DWH.

Setup PowerBI with embadded capacity for customer reporting.

Person should be expert into SQL development & DWH designing, Python and PowerBI

Compétences : Python, Big Data Sales, SQL, Programmation de bases de données, Science des données

Concernant l'employeur :
( 28 commentaires ) New Delhi, India

Nº du projet : #32692251

6 freelances font une offre moyenne de 9550 ₹ pour ce travail


Hi, I'm an experienced data scientist with over 7 years of active development experience building Machine learning and AI systems using multiple tools and technologies including R, Python and PySpark. I hold a Masters Plus

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(78 Commentaires)

I am Phd scholar of computer science and profassioanal data scientist. i have strong expertise in SQL and powerBi tools, i can do this task, can you please share me full task detials.

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(27 Commentaires)

Hi Client , I already done many similar tasks and I can close this task quickly. I’m a Senior Software Developer & Freelance Web & Automation developer with 7+ years of experiences with Master degree holder and expe Plus

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(2 Commentaires)

I have an 5 year of experience in fmcg company . I have devloped many ERP system module from purchase , warehouse to sale module. And also having experience in sql tools work as oracle developer for 2 year .

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(0 Commentaires)

will ensure the solution proposed and tasks for the problem statement easier for future references/usage

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(0 Commentaires)

Data Engineer/Analyst Around 2.5 years of experience in Development, design, and support of applications in Data warehousing, Big data, AWS Technologies along with respective certification, ensuring high data quality Plus

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(0 Commentaires)