Андрій

EDUCATION:
BAIK ANDRII • The National Forestry and Wood-Technology University of Ukraine,
Data Engineer Department of Computer Technology Bachelor’s degree, 2011
• Lviv Polytechnic National University, Department of Computer
Lviv, Ukraine Technology Master’s degree, 2024

[відкрити контакти](див. вище в блоці «контактна інформація») EXPERIENCE:

[відкрити контакти](див. вище в блоці «контактна інформація»)
Data Engineer
SoftServe (2017 – Present):
https://t.me/baikandrew
• Design and implement Data Warehouse architecture using three-layer
structure (Staging, Core, and Data Marts), based on Star and Snowflake
SKILLS: schemas with fact and dimension tables.
• Collaborate with business analysts and product owners to design data
• Oracle Database models and implement technical solutions aligned with business
• MS SQL Server requirements.
• SQL/PL/SQL • Optimize query performance in Azure Synapse by redesigning table
• SQL/T-SQL distribution strategies and indexing (clustered columnstore and no
• DWH clustered indexes), reducing execution time and improving workload
efficiency.
• ETL
• Implement structured tables and business-facing views within a
• SSIS
Lakehouse architecture using Bronze, Silver, and Gold layers to support
• SSAS
scalable data transformation and consumption.
• OLAP
• Build and optimize ETL processes that consume data from multiple source
• Power BI systems with incremental data loading.
• Azure Cloud • Develop multidimensional OLAP cubes with complex calculated
• Azure Synapse SQL DW measures, hierarchies, and KPIs, supporting analytical reporting and
• Azure Data Factory decision-making.
• Azure Data Lake • Design Power BI dashboards integrated with Data Warehouse layer.
• Databricks • Deploy data platform solutions across environments using automated
• PySpark CI/CD pipelines.
• GIT • Manage source control and versioning using Git repositories in Azure
• CI/CD DevOps, following structured branching and pull request workflows.
• English level – intermediate • Design and prepare data validation test cases to ensure data accuracy,
completeness, and consistency across data pipelines.
CERTIFICATIONS: • Prepare technical documentation for client delivery.
• Perform production releases and post-deployment data validation.
• Microsoft Certified: Azure
Fundamentals
• Microsoft Certified: Azure Data Database Developer
Fundamentals KredoBank (2013 – 2017):

• Participated in the development and optimization of banking products,
including deposits, credit operations, and card transaction processing.
• Developed database objects including stored procedures, tables, views,
and triggers to support data platform processing and reporting workflows.
• Optimized existing procedures and processes.
• Prepared scripts for the collection of data for the audit department.
• Developed reports using Fast Report.
• Loaded data into warehouse tables using Oracle Data Integrator to support
structured data ingestion and transformation workflows.
• Collaborated with the different departments of business for the
requirements for new and existing bank products and implement them in
the system.
 • Participated in sprint planning, estimation, and prioritization of tasks in
collaboration with the Product Owner
• Evaluated and discussed technical implementation approaches with the team
Azure DevOps to meet business requirements
Azure Cloud • Designed Data Warehouse schemas and defined relationships between tables
Azure Synapse SQL • Developed and maintained data ingestion pipelines into DWH (Azure
DW Synapse) using Azure Data Factory and Databricks
2022 – Azure Data Factory • Contributed to the design and migration of Azure Data Lake to a Medallion
present Azure Data Lake architecture (Bronze/Silver/Gold layers)
Databricks • Built batch and streaming ETL pipelines
PySpark • Migrated ETL processes from Talend to a modern Azure-based stack (ADF
GIT + Databricks)
CI/CD
• Participated in testing activities, including bug prioritization, root cause
ERwin Data Modeler
analysis, and fixes
Scrum
• Optimize query performance in Azure Synapse by redesigning table
distribution strategies and indexing (clustered columnstore and no clustered
indexes), reducing execution time and improving workload efficiency.
• Deployed solutions to production using CI/CD pipelines in Azure DevOps

• Contributed to Data Warehouse architecture design and data integration
processes
• Defined table structures, relationships, and participated in data modeling
Oracle Database • Analyzed source systems to identify dependencies between business entities
MS SQL Server across multiple databases
SQL/T-SQL • Collaborated with stakeholders to understand business processes and data
2020 – 2022 DWH requirements
ETL • Developed ETL pipelines for data extraction, transformation, and loading
SSIS into DWH
GIT • Performed bug analysis and fixes during testing phases
Waterfall methodology • Deployed solutions to client environments
• Presented implemented solutions and explained technical details to
stakeholders
• Prepared technical documentation and maintained code in version control
systems

• Estimated development effort and timelines based on business requirements
• Proposed and discussed implementation approaches with stakeholders
MS SQL Server • Developed proof-of-concept (PoC) solutions to validate requirements and
SQL/T-SQL approaches
DWH • Designed and maintained ETL processes using SSIS packages and stored
ETL procedures
2017 – 2020 SSIS • Worked with OLAP cubes (SSAS):
SSAS - Designed dimensions and measures
OLAP - Built multidimensional models with complex hierarchies
Power BI - Implemented KPI calculations aligned with business requirements
SVN • Developed Power BI dashboards using OLAP cubes and DWH data
• Identified and resolved issues during testing phases
• Delivered solutions and provided deployment guidelines or performed
deployments