TeamLead BI (Yandex DataLens)

🔖 Automated updating of data marts from MS SQL to ClickHouse (Airflow, Python).
🔖 Conducted an audit of the BI environment. Based on the audit results, we eliminated problems with DataLens performance (made tables columnar, got rid of views, formalized the process of updating tables).
🔖 Supervised the project to move from BigQuery to Yandex Cloud (ClickHouse, Airflow, dbt, AppMetrika, Yandex Metrika). Conducted training for cross-functional teams on working with dbt, ClickHouse and DataLens.
🔖 Built key data marts in ClickHouse for operational analytics and data analysis for key Ecom metrics.
🔖 Managed the team to improve reporting on finance, operations, marketing (key business indicators).
🔖 Participation in a cross-functional project to change the company's main reporting, forming requirements and setting tasks for the team of analysts. Assembled a tree of metrics for the main areas of the Company's activity.
🔖 Developed several key dashboards for C-Level (sales metrics, product analytics metrics, participated in the development of a tree of metrics for reporting using the OKR methodology).
🔖 Stabilized the work of DWH after the departure of data engineers. Hiring a new team. Developed a dashboard for monitoring MSSQL and Windows server metrics in Graphana. Created a project to optimize DWH.

Daily tasks:
☑ Control of data updates in DWH (MSSQL, ClickHouse, GreenPlum) via Airflow in the core layer and data marts;
☑ Formation of data marts for building dashboards in DataLens (T-SQL / Python / dbt) in MSSQL / ClickHouse;
☑ Writing DAG in Airflow for data marts (MSSQL, Airflow + dbt);
☑ Forming AdHoc downloads based on requests from business units (python pandas parquet s3);
☑ Optimizing SQL for building data marts in MSSQL and ClickHouse + dbt;
☑ Mentoring a team for developing reporting in DataLens, developing data marts in MSSQL and ClickHouse;
☑ Managing a team of data analysts (forming a backlog, setting tasks, reviewing SQL and dashboards);
☑ Acting Head of DWH (servicing downloads via AirFlow, optimizing MSSQL and ClickHouse).

Tech Stack: DataLens, sql, python, dbt, airflow, GreenPlum, ClickHouse, Superset, jupyter notebooks, Yandex Cloud, MSSQL, Graphana, Zabbix

🔎 ADDITIONAL
☑ Subject areas: Sales, web, product analytics, Operations, Logistics, Inventory management