I'm a Senior Data Engineer with 5+ years building production data platforms for high-load e-commerce systems. Currently at Wildberries (one of Europe's largest e-commerce platforms), where I design and operate analytics infrastructure processing millions of events per day.

I specialize in the intersection of real-time streaming and analytical workloads — the hard problems that happen when you need both sub-second latency and historical query performance at scale.

PostgreSQL → Debezium CDC → Kafka → Flink → Delta Lake → dbt → ClickHouse → Grafana

Production-grade local data platform — from CDC to ML predictions

A complete end-to-end data platform built with open-source tooling. Demonstrates real-world patterns: exactly-once Flink, Avro schema evolution, Data Contracts, full observability stack, and troubleshooting runbooks.

CDC (Debezium) → Kafka → Flink (exactly-once) → Delta Lake → dbt → Superset + Grafana
                                                                  ↳ MLflow → SageMaker

Key features: Schema Registry · Data Contracts · 5 Troubleshooting Runbooks · GDPR/PII masking · make demo one-command setup

Cloud-native data platform on AWS — Kinesis · Glue · Iceberg · SageMaker

A 12-week portfolio project targeting AWS Data Engineer Associate certification. Implements a full Medallion architecture on AWS: real-time ingestion via Kinesis, S3 Lakehouse with Apache Iceberg, batch processing through AWS Glue + dbt, Flink anomaly detection, and MLOps pipeline with SageMaker + MLflow.

Phases: Foundation → Lakehouse → Batch (dbt) → Real-Time (Flink) → ML (Churn Prediction) → Serving (QuickSight)

Wildberries · Senior Data Engineer / Tech Lead (Dec 2025 — present)

• Designed a 6-layer hybrid Kappa architecture (Ingestion → Staging → Entities → Speed → Batch → Serving) processing 700M+ events/hour from Kafka
• Built sharded ClickHouse cluster: sipHash64 partitioning, Buffer Engine for compaction, ReplicatedReplacingMergeTree for entity tracking
• Introduced Entities layer consolidating status lifecycles across 1.2B+ rows, eliminating full-scans and enabling lineage tracking
• Optimized dashboards: pre-aggregated Serving layer reduced scan volume from 1.2M rows → 1,000 (~1000x speedup)
• Implemented Rolling Backfill with 8-day recalculation window — 100% accuracy under delays up to 186 hours
• Led team of 3 engineers: code review, branching strategy, CI/CD (trunk-based Git)
• Analyzed 13,000+ lines of SQL across 4 business domains, 60+ dashboards, 20+ materialized views

Wildberries · Senior Data Engineer (Apr 2024 — Dec 2025)

• Built Medallion architecture (Bronze/Silver/Gold) from scratch on ClickHouse — first structured data platform for the team
• Designed Data Mesh across 5 products: each department as an independent data domain owner
• Deployed alerting for Kafka, ClickHouse, Airflow with 3-tier escalation (P0/P1/P2)
• Doubled warehouse processing speed, reduced inventory losses by 80%

CandyCat · Senior Data Engineer (Aug 2023 — Jun 2024)

• Built real-time CDC pipeline: Debezium (PostgreSQL) → Kafka → Flink (streaming) + Spark (batch) — reduced data delivery latency from 4 hours to 30 seconds
• Built Apache Iceberg lakehouse with ACID guarantees and schema evolution — reduced storage costs by 35% via compaction and partitioning
• Orchestrated 40+ Airflow DAGs, dbt transformations, Terraform + Docker infrastructure
• Implemented AWS analytics: S3 data lake, Lambda for event processing, EC2 for batch, Redshift for OLAP

Kata Academy · Middle / Senior Data Engineer (Feb 2022 — Aug 2023)

• Built analytics system from scratch: PostgreSQL schema (3NF) + ETL pipelines to ClickHouse
• Created 50+ dashboards in DataLens and Superset for marketing and product teams
• Automated reporting — reduced manual work by 50%, weekly report prep from 8 hours → 15 minutes
• Deployed and administered analytics infrastructure in Yandex Cloud

• 🔨 Production Hardening of the E-Commerce Data Platform: Schema Registry, Data Contracts, troubleshooting runbooks
• 📚 AWS Data Engineer Associate certification (DEA-C01)
• 🤖 Exploring MLOps as a growth path — Feature Stores, model monitoring, retraining pipelines
• 📝 Writing ADRs (Architecture Decision Records) on Flink vs Spark, Delta Lake vs Iceberg

I'm actively looking for remote Senior/Staff Data Engineer roles at international companies — particularly those working on real-time data platforms, streaming analytics, or MLOps infrastructure.

Interested in: Tinybird · DoubleCloud · Altinity · adtech/fintech scale-ups