data engineer for eCommerce

The project modernizes, maintains, and develops an eCommerce platform for a large US-based retail company serving millions of omnichannel customers each week. Product teams focus on Customer, Loyalty, Search and Browse, Data Integration, and Cart. Current priorities include onboarding new brands, re-architecture, database migrations, and migrating microservices to a unified cloud-native solution without disrupting business.

• Implement a solution for a large retail company
• Support the processing of large data volumes and integrate the solution with the current architecture

• 8+ Years of overall experience
• 3+ Years of recent, hands-on experience with Azure Data Factory and Synapse
• Strong expertise in designing and implementing conceptual, logical, and physical data models
• Strong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, and PySpark
• Extensive experience building scalable ETL/ELT pipelines for data lakes or data warehouses
• Ability to integrate data from databases, APIs, and external data providers using API integration or message queuing
• Proficiency in data warehousing solutions, including dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, and Data Vault
• Proficiency in SQL for complex queries, data transformations, and performance tuning on cloud-based data storage
• Experience integrating metadata and governance processes into cloud-based data platforms
• Experience with cloud-based analytical databases
• Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix
• Experience with Python and Python-based ETL tools
• Demonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and communicate with stakeholders at all organizational levels
• Будет плюсом: Azure, Databricks, or other relevant technology certifications, Bash/Unix/Windows shell scripting, Elasticsearch, Docker, Kubernetes, troubleshooting and performance tuning of data workflows and pipelines, collaboration with stakeholders and cross-functional teams, planning, estimating, and tracking feature implementation, Computer Science and data science academic credentials

• Условий в вакансии нет