CV Data Engineer
Name: Aleksandr Bazhutov
Position: Database Engineer / Data Engineer
Location: Georgia (Remote)
English: B2
Russian: Native
Summary
Database Engineer with 7+ years of experience in Oracle, Firebird, and ClickHouse. Deep focus on SQL/PLSQL development, ETL pipelines, performance optimization, and data modeling for high-load systems. Consistent record of reducing execution time of critical operations by 10×–70×, refactoring legacy logic, and stabilizing transactional systems. Strong engineering discipline: version control, CI/CD, containerization, reproducible environments.
Showcase: ClickHouse Query Optimization (go to 70× faster )
Core Skills
SQL, PL/SQL, Oracle Database, Firebird SQL, ClickHouse, ETL Design, Data Modeling, Query Optimization, Stored Procedures, Transactions, Python (ETL automation), Airflow (conceptual), Git, Docker, Kubernetes, CI/CD, XML/JSON, XSD, REST, Jasper Reports, APEX
Experience
Senior Database Engineer
Medical Insurance Company “Arsenal”
Jan 2020 — Aug 2025
– Built a parallelized ETL pipeline for FIAS address dataset; full load time reduced from 8 hours to 30 minutes.
– Replaced legacy KLADR search with Lucene++ UDR; reduced query time from 20 seconds to 0.5 seconds.
– Eliminated database-wide locking by redesigning the ID generation mechanism from procedural numbering to generator-based allocation.
– Designed, refactored, and optimized complex PL/SQL packages, procedures, and functions for core business logic.
– Stabilized transactional workloads by removing bottlenecks in indexing, triggers, and procedure execution paths.
– Maintained cross-system integrations (XML, JSON, API endpoints) and ensured data consistency across operational modules.
Database & Web Developer
Insurance Company “Arsenal”
Oct 2018 — Dec 2019
– Developed internal web application using Oracle APEX + PL/SQL for transport insurance and travel insurance modules.
– Reduced business-logic change cycle from 1–2 days to 1–3 hours by eliminating hardcoded logic and restructuring procedures.
– Implemented interval partitioning for high-volume transaction tables; report generation speed improved from 30 seconds to 3 seconds.
– Converted multiple asynchronous business processes into deterministic data-driven logic, reducing operational error rates by ~90%.
– Introduced Git-based workflow, ensuring traceability, code review, and stable deployment processes.
Selected Achievements
– Query performance improvements up to ×70 across high-load modules.
– Legacy system modernization: from mixed procedural/hardcoded logic to maintainable structured PL/SQL architecture.
– Full ETL redesign for large government datasets (FIAS, KLADR → Lucene++), achieving near-real-time availability.
– Multi-database ecosystem experience (Oracle, Firebird, ClickHouse) with consistent optimization patterns applied.
Responsibilities Aligned with Data Engineer Role
– Designing scalable datasets and models for analytics and operational systems.
– Building ETL workflows and data pipelines with strict performance constraints.
– Refactoring and optimizing SQL and PL/SQL at scale.
– Implementing data quality, data validation, and reproducible transformations.
– Working across development, analytics, product, and operations to ensure data readiness.
– Applying DevOps practices: containerization, CI/CD, environment reproducibility.
Tools & Technologies
Oracle | PL/SQL | Firebird | ClickHouse | SQL | Python | Airflow (conceptual) | Git | Docker | Kubernetes | Jenkins | GitLab CI | XML | JSON | REST | APEX | Jasper Reports