Lead Data Architect

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 Architect 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 Must have:

• Readiness to work until 8.00 pm CET (no need to do overtimes)
• Overall years of experience required 8+ (at least 1+ year in an 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.

Nice to have:

• 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.
• Ability to plan, estimate and track progress of implementing features
• Computer Science and data science academic and education credentials