Radu Gheorghiu

Rising Codementor

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ABOUT ME

I am curious to know the world and I like to use data to explain it

I am a Software Engineer who enjoys working with data. Be it storage, administration, querying, analyzing, processing, I believe data is the best tool we have in answering all questions.

This is why I have devoted myself to learning and touching all aspects of the software ecosystem that works and handles data, for diverse reasons.

I enjoyed starting my career as a Report Developer, learning how to display data and transform it into useful information.

Then I moved on to the admin side of things to tackle problems and solve them so that the data is stored correctly and is easily accessible and fast.

My next challenge would be a step up from the Reporting role to a modern way of working with data into data analytics, data science and machine learning.

I always try to keep myself in the loop with the newest technologies from these 3 categories which I believe create the data lifecycle:

acquire and store data
clean, process and analyze data
consume the data (either through direct visualization in a report or as a result obtained from a ML model)

English

Bucharest (+02:00)

Joined August 2020

EXPERTISE

SQL

10 years experience

Python 3

5 years experience

Machine learning

3 years experience

PyTorch TensorFlow NumPy

PyTorch TensorFlow NumPy Pandas Matplotlib Seaborn

Data Engineering

5 years experience

Apache Airflow Amazon S3 Amazon Redshift

Apache Airflow Amazon S3 Amazon Redshift Apache Spark

Python

6 years experience

Data modeling

7 years experience

Data warehouse

5 years experience

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SOCIAL PRESENCE

GitHub

ai21labs-hackathon

Python

riley-goodside-scale-ai-event

Stack Overflow

20389 Reputation

110

EMPLOYMENTS

Data Engineer

Accesa

2020-05-01-Present

I work as a Data Engineer on an IoT project, where measurements data from pools are read from multiple transactional databases into a Del...

I work as a Data Engineer on an IoT project, where measurements data from pools are read from multiple transactional databases into a Delta Lake in Azure. The Databricks Delta Lake contains multiple Databricks notebooks with Spark code that ingest data from transactional MySQL databases and process this data to output information used in PowerBI reports. I handle building the ETL pipelines and job schedules, creating the data sources that are needed for the PowerBI reports and also help with creating and deploying the PowerBI reports in the online service.

Azure

Python 3

Apache Spark

Azure

Python 3

Apache Spark

Power BI

Data Architect

Accesa

2019-07-01-2020-05-01

Worked as a Data Architect to create the data model, ETL processes and outlined the documentation template for migrating data stored in a...

Worked as a Data Architect to create the data model, ETL processes and outlined the documentation template for migrating data stored in an old DBASE database to SQL Server 2016. Created custom T-SQL Scripts and migration pipelines automated with Azure DevOps that allowed versioned T-SQL scripts to be ran and create specific versions of databases for the application developers. During my time on the project I outlined the general data model, set up documentation best practices using Enterprise Architect, created T-SQL templates that could be called from SQLCMD, templates which could be "injected" with specific table-based migration logic. I handled discussions with the client, discovery sessions and laid out the general plan and major milestones that needed to be hit in order for the project to be able to continue in a straightforward way, without much further involvement from my side.

Microsoft SQL Server

Data Scientist

Accesa

2018-10-01-2019-07-01

Worked as a Data Scientist and led a team of 3 Master's students in developing data analysis pipelines and doing data analysis on data fr...

Worked as a Data Scientist and led a team of 3 Master's students in developing data analysis pipelines and doing data analysis on data from a factory's production line. The end goal was to create a prediction model to predict faults in the production line so that preventative maintenance could be done in order to minimize the number of faulty parts at the end of the production cycle. The end goal has not been achieved during my time on the project due to the low quality of the data. However, important steps were made in analyzing the data, creating the data model and ETL processes for reading, processing and storing the data from the original .CSV files streamed to our system to a MongoDB based data-store.

MongoDB

NumPy

Pandas

MongoDB

NumPy

Pandas

Python 3

TensorFlow

Keras