Enterprise Data Warehouse Migration & Recommendation Systems
Key Expertise
Experience
10+ years
Timezone
CET (UTC +1)
Skills
Languages
Databases
Infrastructure
Frameworks
Integrations & Protocols
Overview
Data platform modernization for one of the largest US retail chains, spanning over a thousand physical stores and a major e-commerce operation. The scope covered legacy warehouse migration, recommendation pipeline rebuilding, and data governance implementation – all across a petabyte-scale environment without disrupting ongoing retail analytics.
Achievements
Reduced average processing time on recommendation and user interaction pipelines after migrating them to modern cloud infrastructure. Built a disaster recovery tool for the metadata and lineage environment that became the standard cross-team onboarding reference, replacing a previously manual and undocumented process.
Responsibilities
- Technical migration of an enterprise data warehouse from multiple legacy database systems to a cloud-native solution, preserving full metadata and lineage coverage across petabyte-scale retail data.
- Migration of a substantial share of ETL pipelines for recommendation and user interaction systems from legacy distributed processing to modern cloud orchestration and warehouse infrastructure.
- Refactored the internal DAG-building framework, meaningfully improving maintainability and reducing the cognitive overhead of pipeline development across the team.
Technologies Used
Key Expertise
Experience
10+ years
Timezone
CET (UTC +1)
Skills
Languages
Databases
Infrastructure
Frameworks
Integrations & Protocols
This project was delivered by
Dmytro K.
More Projects by Dmytro K.
Cloud Data Platform for Neobank
Senior Data Engineer
End-to-end cloud data platform for a fast-growing neobank, with core event tables ingesting large volumes of data daily and hundreds of terabytes of cumulative data. The platform underpins reconciliation, partner integrations, and financial reporting – operating on a cloud-managed infrastructure where both reliability and regulatory compliance are non-negotiable. Given the nature of the business, any pipeline failure or data discrepancy carries direct financial and audit consequences.
Multi-Asset Market Data Platform
Senior Data Engineer
Mission-critical market data platform covering equities across dozens of global exchanges, FX, and fixed income, serving both internal quantitative trading desks. At this scale and in this context, reliability is not a quality attribute – it is the product. The system had to sustain consistent ingestion and low-latency access during peak trading hours across multiple time zones, with no tolerance for data gaps or processing delays that could affect trading decisions.
Ready to Build Your AI Team?
Get matched with the right AI experts for your project. Book a free discovery call to discuss your requirements.
We respond within 24 hours.