Technical Stack: Apache Airflow, ClickHouse, PostgreSQL, dbt, Git, Python, Apache Spark, Apache Kafka, MinIO Design and implement scalable data infrastructure supporting enterprise-wide analytics and business intelligence initiatives. Lead development of data-driven and event-driven architectures handling data ingestion from 120+ diverse sources into a centralized data lake. Key Responsibilities: - Orchestrate complex data pipelines using Apache Airflow to automate ETL/ELT workflows across multiple data sources - Build and maintain robust data lake infrastructure utilizing MinIO for object storage and managing raw data layers - Develop and transform data models using dbt (data build tool) to create clean, reliable data marts for downstream analytics - Implement real-time event streaming pipelines with Apache Kafka for event-driven data processing - Design and optimize data warehousing solutions across ClickHouse and PostgreSQL databases - Process large-scale datasets using Apache Spark for distributed data processing and transformation - Develop Python-based data processing scripts and automation tools to enhance pipeline efficiency - Manage version control and collaborative development workflows using Git - Create structured data layers (raw, staging, marts) following data warehouse best practices - Enable business intelligence by delivering curated datasets to visualization dashboards and reporting tools

Developed comprehensive warehouse reporting solutions to enhance operational analytics and business intelligence capabilities for one of the largest e-commerce platforms. - Designed and implemented warehouse analytics reports to improve operational efficiency and data-driven decision-making - Built scalable data pipelines using Apache Airflow for automated report generation and data processing workflows - Developed high-performance analytical queries and data models in ClickHouse for real-time warehouse operations reporting - Processed large-scale warehouse data using Apache Spark for distributed computing and complex transformations - Managed code versioning and collaborative development through Git workflows - Optimized query performance and data storage strategies to handle high-volume warehouse transaction data - Collaborated with business stakeholders to identify key metrics and reporting requirements

- Deploying dump files in Clickhouse DBMS/Oracle; - Writing intermediate queries in Clickhouse DBMS (occasionally with the help of Pentaho and Knime); - Creating workflows on Analytic platform KNIME by gathering informations from databases; - Updating tables, schemas in Clickhouse DBMS using transformations and scheduled jobs in Pentaho Data Integration; - Building data marts, charts, widjets, dashboards; - Visualizing data with the likes of Apache Superset and A2Data. - Building pipelines and schedule dags in Apache Airflow.

Разработал решения для интеграции данных из различных источников и систем, оптимизировал скрипты, что позволило улучшить аналитическую отчетность и принятие решений. Автоматизировал все отчеты с помощью Apache Airflow и так же настроил версионность кода GitLab.

Работа с базой данных, редактирование сайта.