Custom Python-development for solving tasks of any complexity!

Submit a request for custom python-development

Leave a request

Using Python and Airflow for building data pipelines

No more command line or XML black magic! Use standard Python functions to create workflows, including date and time formats for scheduling and loops for dynamic task creation. This allows you to maintain complete flexibility when building workflows.

Why Python?

Reliable integrations

Airflow provides a plethora of plug-and-play operators ready to perform your tasks on Google Cloud Platform, Amazon Web Services, Microsoft Azure, and many other third-party services. This makes it easy to apply Airflow to existing infrastructure and expand the capabilities of next-generation technologies.

Anyone who knows Python can set up a workflow. Apache Airflow doesn't limit the scope of your pipelines; you can use it for creating machine learning models, data transfer, infrastructure management, and much more.

Easy to use

Get a personalized CP + 15% discount on services

What can we offer you?

Полное сопровождение данных, контроль и учёт разрозненностей версий и форматов, протоколов и форм

Data source integrations

Creating data quality management services in the storage

Data quality management

We employ new methods of data movement and orchestration, reducing the risk of data loss or distortion

Data orchestration

Based on applied development in Python and Apache Airflow, it is possible to replace expensive proprietary Western solutions with domestic alternatives

Import substitution of Western software

By leveraging Airflow and custom Python extensions, it's possible to automate the construction of pipelines and reduce development costs for a single data integration. Our team has the necessary expertise and a proprietary data integration automation framework built on Apache Airflow

Building automation frameworks for data pipelines for a large number of teams