Aleksei Pisarov

I develop and maintain corporate DWH and ETL processes. Volume of DWH is 60 TB. List of sources: PostgreSQL, Google BQ, Hana, etc. In my work I use Greenplum, SAP DS, Python.

Created a corporate DWH and tabular model from scratch. Configured data cleaning and integrity checks, as well as ETL processes. The volume of DWH is 3 terabytes and fastly grow, the volume of the tabular model is 10 gigabytes, the largest table in tabular model has 600 million rows, all systems were stable and have worked fastly. In my work I used SSIS, SSAS (Tabular), MS SQL, T-SQL, PowerBI, Python, Jira, Confluence. For DWH we've used the Inmon approach.

I put the maintenance plans in order (there was no integrity check, work with indexes, statistics, etc.), changed the server and database settings to optimal ones, eliminated deadlocks in the system. Optimized stored procedures and many Adhoc queries, now they are executed several times faster. Created a normal recovery plan, gave value to RTO and RPO and Baseline for counters, etc. In my work I used MS SQL, T-SQL, SSIS, SSRS and Symantec NetBackup 7.5 (configuring and administering)