Фуад Гусейнов

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.

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