Lead Data Engineer / Data Architect

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.

• Mandatory Skills Description:

  • Readiness to work until 8.00 pm CET (no need to do overtimes)
  • Overall years of experience required 8+ (at least 1+ year in a Lead/Architect position)
  • 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.
  • 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.
  • Demonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels.