About

My name is Peter Lalovsky and i am Canada based, multilingual (English, French, Russian, Bulgarian) Databricks, Microsoft SQL Server certified professional with more than 20 years experience in IT, including the last 10 years in Data Engineering and Business Intelligence (BI).

My Expertise

• Perform analysis, design, development and integration tasks
• Data modeling (Data Vault; Star Schema; Bridge, Junk Dimensions; Data Snapshot; Entity-Attribute-Value) using modern BI tools on Azure (ADF, Synapse, Databricks, Fabric, Power BI)
• Architect and develop big-data fully automated backend ETL solutions in Databricks and Azure Cloud, include full log, error handling and error reporting
• Data ingestion by using multiple data sources – structured, semi-structured, non-structured, API, flat files and others
• Build reports and documentations of the back-end solutions
• Develop backend automations with Databricks, Azure, SSIS, API, PowerShell, Python, C#
• Focused on results, efficiency and customer satisfaction

Examples of my data solutions

• ETLs that ingest data from various data sources, cleanse and transform and validate data, based on flexible and dynamic rules, create data warehouse
• Integrations to migrate and transformation data from the current version of the application to the new one; integrate the data between AVEVA PI System into Ekhosoft
• Core functionality as backend component (Rule manager)
• Automatons to exchange of data between databases on scheduled basis; Determine and process only the upserted SSAS partitions
• Optimizations as build reusable frameworks that save development and deployment time; rewrite code to tale less execution time and resources.
• Reporting with Power BI, Tableau, SSRS
• Migrate legacy systems to Azure, SAS to Databricks

The Book

I am the author of the book Learn Microsoft SQL Server Intuitively. Transact-SQL: The Solid Basics, intended for Beginner/Intermediate audience and I am also constantly learning and exploring new technologies to be able to cover the evolving need of the data manipulation, transformation and representation.

The Technologies