Descripción de la oferta
Project Description: The primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week. Solutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart. Current overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business. Responsibilities:We are looking for Data Engineer who will be responsible for designing a solution for a big retail company. The main focus is to support processing of big data volumes and integrate solution to current architecture. Skills Description: • Readiness to work until 8.00 pm CET (no need to do overtimes) • Overall years of experience required 8+ • Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). • Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. • Hands-on experience with Power BI, including data modeling, report and dashboard development, and building interactive, business-ready visualizations based on enterprise data sources. • Strong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions. • Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. • Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. • Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) • Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. • Experience integrating metadata and governance processes into cloud-based data platforms • Certification in Azure, Databricks, or other relevant technologies is an added advantage • 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. • Experience with shell scripting in Bash, Unix or windows shell is preferable. Nice-to-Have Skills: • Experience with Elasticsearch • Familiarity with containerization and orchestration technologies (Docker, Kubernetes). • Troubleshooting and Performance Tuning: Ability to identify and resolve performance bottlenecks in data processing workflows and optimize data pipelines for efficient data ingestion and analysis. • Collaboration and Communication: Strong interpersonal skills to collaborate effectively with stakeholders, data engineers, data scientists, and other cross-functional teams. Languages: English: B2 Upper Intermediate
