Data Warehouse (DWH) Concept Development.Developed the concept for a data warehouse solution.DWH Implementation: PostgreSQL + Airflow.Implemented the data warehouse using PostgreSQL and Airflow.Data Structure Analysis for Warehouse Architecture Design.Analyzed the structure of the utilized data for warehouse architecture design, including data layering, normalization, and structuring.Data Mart Construction for Tableau Integration.Constructed data marts for seamless integration with Tableau.Alerting Systems Implementation for Airflow DAG Behavior.Implemented alerting systems for monitoring Airflow DAG behavior.Data Quality Alerting System Implementation with Slack Integration.Developed a data quality alerting system for quantitative data checks with Slack notifications.Reporting Implementation: From Basic Totals to Complex Cohort Analysis using SQL.Implemented reporting systems ranging from simple total reports to intricate cohort analysis utilizing SQL.Database Maintenance System Implementation.Implemented a database maintenance system, monitored server behavior, and collaborated closely with DevOps for software version updates (PostgreSQL server, Apache Airflow, Tableau).Dockerfile and docker-compose Files Enhancement for Autonomous Development and Testing.Enhanced Dockerfile and docker-compose files for autonomous development and testing, including version upgrades from 2.2.1 to 2.3.3 and 2.3.3 to 2.5.0.Custom Operator Development for External Data Source Integration.Developed custom operators for interacting with external data sources.Employee Training and Mentorship in the BI Department.Provided training and mentorship to new hires in the BI department, including junior data engineers, BI engineers, and data analysts.Participation in Hiring Processes for Department Expansion.Conducted interviews for new hires during department expansion.

Data Storage Architecture Development for the Project and its BranchesDesigning and developing integration systems with the customer's information systems.Training the team to work with NoSQL solutions.Conducting research to identify optimal methods for data storage and processing.Optimizing the load for PostgreSQL and MongoDB.Configuring data storage systems on the customer's premises.Setting up integration systems on the customer's premises.

Implementing Enhancements to the Bank's Current Internal Information System Using T-SQLDeveloping Data Pipelines, Data Processing, and Data Cleansing Systems:Designing and implementing workflows for data extraction, transformation, and loading (ETL).Building systems for automated data validation and cleansing to ensure data quality.Creating Architectural Designs and Participating in the Development of a Prototype Service-Oriented System to Replace the Current One Using .NET Core:Designing the overall system architecture, including microservices and RESTful APIs.Collaborating in the development of a prototype to demonstrate the system's functionality and scalability.Conducting Internal Training for Employees on Working with MS SQL Server Databases:Organizing and leading training sessions focused on database management, query optimization, and advanced T-SQL techniques.Providing hands-on workshops to enhance practical skills and problem-solving abilities.Implementing Development Using MS Visual Studio Database Project:Utilizing MS Visual Studio Database Projects for version control, schema management, and deployment.Ensuring consistent and reliable database deployments across different environments.Developing and Implementing CI/CD Processes for Databases Using sqlpackage (.dacpac) and Jenkins:Setting up continuous integration and continuous deployment (CI/CD) pipelines for database changes.Automating the build and deployment process using sqlpackage to create and deploy .dacpac packages.Integrating Jenkins to manage the automation workflows, including testing and validation steps.

Development of Infrastructure for High-Load MS SQL DatabasesQuery Optimization:Analyzing and optimizing SQL queries to enhance performance and reduce execution times.Implementing indexing strategies and rewriting queries to improve efficiency.Data Storage Normalization:Structuring databases to eliminate redundancy and improve data integrity.Designing data models for efficient management and retrieval.Developing Data Pipelines Using ETL Technologies (SSIS, Informatica):Creating ETL processes to extract, transform, and load data from MS SQL, Teradata, Oracle, and Excel.Ensuring data consistency, quality, and timely availability.Developing Data Structures for Corporate Reporting:Designing schemas and structures to support corporate reporting and analytics.Implementing data warehousing solutions for comprehensive analysis.Developing Infrastructure for Corporate Information Systems:Building and maintaining technical infrastructure for robust and scalable systems.Ensuring high availability, security, and performance of databases.Optimizing SQL Queries:Continuously refining SQL queries for optimal performance.Using performance tuning techniques to resolve issues.Identifying Bottlenecks:Detecting and mitigating performance bottlenecks in databases and applications.Collaborating with OOP Developers:Working with OOP developers to design and implement database architectures.Aligning database designs with application requirements.Training New Personnel:Providing training on database technologies and best practices.Conducting workshops and hands-on sessions for new hires.Supporting Information System Elements:Maintaining and troubleshooting components of corporate information systems.Ensuring system stability and performance through proactive support.