Data Analyst, BI Engineer, Product Manager.

6 years in marketing and IT
10 + freelance projects
changed 10 companies in hiring

Technology stack:
Systems: Linux, macOS, Win
Languages for working with data: T-sql (for sms), Python
Libraries: Pandas, Numpy, Matplotlib,unicodecsv, Sqlalchemy
For tracking settings in GTM: html, CSS.
Calculations and operations: Pandas, numpy and sql are less popular.
Virtual environment: Anaconda, conda
Visualization: Matplotlib, Google DataStudio
Bi: Power BI, Tableau etc.
Analytics: Adjust, Mixpanel, Google Analytics, Flurry, AppMetrika
ETL Platforms: OWOX, MyBI
Marketing Automatization: Alytics
Versioning: GIT + Bitbucket + Sourcetree (github+atom, too, but I like it less)
Working with formats: Excel, CSV,JSON for example, using ORM using the Sqlalchemy library
API-ODBC, pyodbc
Serverless: Google BigQuery, Microsoft Azure, Digital Ocean
Containers: Docker, Portainer
Infustructure: Jira,Trello, Confluence, Basecamp

DS trained in connection Atom - GIT - Sourcetree - Bitbucket- Anaconda - Jupyter Notebook

I have experience from trainee web analyst to head of department (head of analytics), in addition i had freelance projects as a product manager

I can do a little DS , back-end, ci-cd. I'm a web-app data analyst by profession, but I got bored with it for so many years, I've done a lot of different projects on Google Analytics, so I'm moving into programming through Python and other data-related languages ... However, while without machine learning, this is still a different direction already.

Yourbet.com
Modulbank.ru
Realweb.ru
Icontext.ru (as part of Webprofiters.ru)
RemontExpress.ru
absolutins.ru
cmc.moscow


Plus, I worked with data warehouses-starting from banal on-premise small servers on sql, ending with azure and BQ clouds.I had experience coming up with a data storage architecture for fintech companies - insurance and digital bank.