Fatkhullakh Turakhonov

I’m a Data Engineer with hands-on experience building end-to-end data pipelines, lakehouses, and analytics platforms across e-commerce, mobility, and retail. I focus on practical, business-ready delivery—modeling, orchestration, and reliable reporting that teams can trust.

In my recent role, I built an end-to-end lakehouse for a Central Asian e-commerce client by ingesting multi-source data into a Medallion architecture on S3-compatible object storage with Delta Lake. I designed and ran a 2-worker PySpark cluster for deduplication, currency normalization, and timezone fixes across 5M+ records, then strengthened the Gold layer with dbt (15 models, 50+ tests) and CI/CD via GitHub Actions.

I deliver resilience as well as performance: I used Delta Lake time travel to recover from a payment schema incident with zero data loss and zero pipeline downtime. I also orchestrate pipelines end-to-end with Apache Airflow (DAG dependencies, retries, SLA monitoring), applied Parquet partitioning to reduce query time by 60%, and delivered Power BI dashboards tracking regional revenue, cohort retention, marketing ROAS, and payment health across all clients.

Before that, I designed a hybrid data warehouse following Inmon (3NF) and Kimball principles (Landing/Staging/Mart) and built ETL pipelines in PL/pgSQL with full Slowly Changing Dimension (SCD Type 2) logic. My experience spans Python/SQL ETL, data quality testing, and BI delivery (Power BI/Tableau), and I’ve also built production-ready application backends (e.g., Spring Boot + PostgreSQL) where clean data and reliable integrations matter.