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Backend Engineer

Rate, USD
Not specified
Work schedule
Full Time,
Language skills
English, Russian, Ukrainian
Available for Hire
Yes
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About me

I am a Backend Engineer with extensive experience in building scalable and reliable distributed backend systems. Over the past few years, I have worked on complex payment APIs, ensuring concurrency-safe database operations and structured logging to guarantee accurate and auditable financial transactions. I am passionate about diagnosing and resolving performance bottlenecks, as demonstrated by my success in addressing a significant production latency regression through root-cause analysis and targeted optimizations.

My expertise extends to provider integration analysis, where I author detailed functional and technical specifications to ensure seamless data transformations and edge-case handling across distributed payment flows. I am proficient in build automation pipelines, having contributed to reducing production release cycles significantly by optimizing CI/CD workflows.

I have experience working in Agile and Scrum environments, collaborating effectively with distributed remote teams using tools like Jira and Confluence. Additionally, I have worked as a Data Engineer on contract, processing and standardizing large datasets with NLP-assisted parsing and rule-based matching, delivering validated and well-documented data mappings.

During my academic tenure as a Research Assistant, I designed and maintained ETL pipelines for large-scale econometric research, handling terabytes of data and building statistical models using Python and Stata. I have also developed open-source projects that combine modern technologies such as Next.js, .NET 8, and GPT-based models to create advanced retrieval-augmented generation systems.

I am skilled in multiple programming languages and frameworks, including C#, Go, Python, TypeScript, ASP.NET Core, and gRPC. My database expertise covers MS SQL Server, MongoDB, PostgreSQL, and Redis, complemented by infrastructure knowledge in Docker, Git, and CI/CD pipelines. I am fluent in English and Russian, with intermediate proficiency in Ukrainian, and I am continuously seeking to expand my technical skills and contribute to impactful projects.


Professional area



Education

Sep 2025 – Exp. Dec 2026 Master of Economic Analysis @ University of Cyprus
Aug 2020 - May 2024 Bachelor of Science in Economics @ Georgetown University in Qatar

Two-time winner, Qatar Collegiate Programming Competition (QCPC) — 2021, 2022


Experience

Dec 2024 – Sep 2025 Backend Engineer @ Altery Payments

Implemented crypto pay-in and refund APIs in a distributed backend; applied idempotent operations, concurrency-safe DB updates, and structured logging to guarantee correct, auditable money movement. Diagnosed and resolved a 10x production dashboard latency regression through systematic root-cause analysis; applied targeted indexing strategies, query rewrites, and request batching. Led provider integration analysis for a crypto pay-in product; authored functional and technical specs covering field-level data contracts, transformation rules, and edge-case handling across distributed payment flows. Contributed to NUKE (.NET) build automation pipeline, cutting production release cycle from 4–6h to 1h. Delivered within an Agile/Scrum workflow using Jira and Confluence across a distributed remote team.

May 2025 – Jun 2025 Data Engineer (Contract) @ International Labor Organization

Processed and standardized 150k+ skill and occupation records using NLP-assisted parsing and rule-based matching; delivered validated mapping tables with full data lineage and documented decision logic.

Feb 2022 – Jul 2024 Research Assistant @ Georgetown University

Designed and maintained ETL pipelines processing 1TB+ of airline and macroeconomic data; enforced schema contracts and reproducibility standards for longitudinal econometric research. Ingested and processed 17GB+ of labor-market text corpora; built statistical models in Python/Stata with documented transformation logic; compiled a 173-country panel for an EFMA 2023 crypto-trading study.


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