Фуад Гусейнов

Junior Data Engineer specializing in the end-to-end data lifecycle; from requirements gathering and 3NF/Star Schema modeling to automated data cleaning and advanced visualization. Proficient in Python, SQL, and PySpark, with a focus on transforming complex datasets into actionable BI dashboards. Familiar with cloud ecosystems and infrastructure, with practical experience deploying data solutions within the AWS environment.

AI & Data Analytics Engineering Researcher at EPAM SYSTEMS (2024-10 – Present)

• Researched and benchmarked emerging Spec-Driven Development (SDD) methodologies to identify best practices and industry standards.
• Conducted analysis on cost optimization techniques within SDD to enhance efficiency and reduce overhead.
• Developed an AI-driven Proof of Concept (PoC) system to migrate and measure costs for SQL objects from Oracle to Postgres migration.
• Evaluated self-learning methodologies for AI models to enhance the autonomous error-correction capabilities

Junior Data Engineer at EPAM SYSTEMS (2025-09 – 2025-12)

• Engineered PySpark ETL pipelines in Databricks to process marketplace data for a major FDA-approved drug release.
• Developed Tableau dashboards to track "Voice of the Customer" metrics and marketplace performance.

Junior Data Engineer at EPAM SYSTEMS (2024-10 – 2025-06)

• Designed hybrid DWH architecture using Inmon & Kimball methodologies as part of a comprehensive lab course, implementing 3rd Normal Form (3NF) and Star Schema models.
• Developed Python-based ETL scripts to process, clean, and ingest diverse data sources (.csv,.xlsx,.txt) into an AWS (S3, EC2, RDS) ecosystem.
• Gained deep hands-on experience with PostgreSQL, mastering advanced database concepts including table partitioning, configuring foreign tables, and writing complex aggregations and window functions.
• Implemented database logic and normalization workflows, authoring stored procedures and optimization scripts to streamline data transformation tasks.
• Built Power BI dashboards to visualize key metrics, effectively translating laboratory data processing outputs into clear analytical insights.

Computer Science – National University Zaporozhye Polytechnic (2023 – 2027)