for the machine learning annotation team. The task is to build and maintain ETL pipelines that automate data movement from raw datasets to the delivery of annotated results to ML analysts.
Tasks:
- Development and maintenance of data annotation ETL processes
- Automation of data validation, collection, and conversion processes
- Support of existing pipelines
- Communication with the client, clarification of technical requirements
- Providing support to internal consumers on technical issues related to data annotation processes
Requirements:
- 1+ year of experience as a Data Engineer / Data Analyst / ETL Developer
- Solid knowledge of PostgreSQL fundamentals
- Ability to write fast asynchronous code in Python (asyncio, pandas, sqlalchemy, apache airflow)
- Knowledge of basic concepts and principles of DWH design and construction
- Solid understanding of working with the Linux terminal
- Knowledge of git
Conditions:
- Comfortable modern office in Tolyatti, ul. Transportnaya, 26a
- Opportunity to switch to a hybrid work format
- Annual salary review and annual bonus
- Corporate gym and recreation areas
- Over 400 educational programs from SberUniversity
- Adaptation program and manager support at the start
- Extended voluntary medical insurance, preferential family insurance, and corporate pension program
- Flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- Prime subscription with the ability to share with three close people
- Referral bonus for recommending friends to the Sber team
Skills:
- PostgreSQL
- Python
- asyncio
- pandas
- SQLAlchemy
- Apache Airflow
- DWH
- Linux
- git
- ETL
