Golov Nikolay

Biography

Graduate of the Faculty of Computational Mathematics and Cybernetics of Moscow State University with a degree in Mathematical Forecasting Methods. Graduate student at the Higher School of Economics, where since 2010 he has also taught at the Department of Business Informatics. He is engaged in scientific research in the field of modern methodologies for building data warehouses (Data Vault, Anchor Modeling), and also studies the use of blockchain technologies in the field of information storage and processing.

He began his career as a programmer at Luxoft, then held senior positions at Forecsys, LANIT, VTB Factoring.

From 2013 to 2019, he led the Data Platform direction at Avito, where he was responsible for building and developing the data platform: from storage systems (including PostgreSQL, MongoDB, Redis, Tarantool, VoltDB) to streaming and queues (Spark, RabbitMQ, NSQ). Served as Chief Data Architect at ManyChat

2025: Director of Product at Postgres Professional

Postgres Professional on October 31, 2025 announced the joining of Nikolai Golova, one of the Russian experts on data architecture, to the team. Nikolay took the position of Product Director of Tengri Data Platform and will be responsible for the development of this product area in the company, as well as for the implementation of advanced approaches in the field of data management.

The appointment accompanies an important strategic step of Postgres Professional - entering the corporate analytics market with the Tengri Data product. It is an enterprise platform for storing, processing and analyzing data up to 10 petabytes, developed in Russia and focused on large companies and government organizations.

Unlike traditional solutions based on Greenplum, Tengri Data is built on the OpenLakehouse paradigm and combines the principles of separation of computing and storage (Compute/Storage). Data is stored in S3 object storage for flexibility, scalability, and high performance even under extreme loads.

The platform supports SQL for data transformation, Python for analytics, machine learning and artificial intelligence, as well as standard connection protocols. Thanks to this, companies can use Tengri Data without overhauling existing processes and without the cost of retraining employees.

{{quote 'All my life I have been building analytical platforms for large organizations. In recent years, when advising large companies, I have faced a shortage of a platform comparable to Snowflake, which any organization can deploy on its servers, or in a private cloud. Solving this problem, we have created the analytical platform Tengri, which is now developing in Postgres Professional. I believe that in 2025 it is strange to limit analysts in working with data, by place, complexity or number of requests. We are able to create a single analytical space where everything can be done with data - Nikolai said about the prospects of Tengri Data Platform. }}