Lead Data Engineer

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., 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.

Must have

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

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.

Luxoft, a DXC Technology Company, (NYSE: DXC), is a digital strategy and software engineering firm providing bespoke technology solutions that drive business change for customers the world over. Luxoft uses technology to enable business transformation, enhance customer experiences, and boost operational efficiency through its strategy, consulting, and engineering services. Luxoft combines a unique blend of engineering excellence and deep industry expertise, specializing in automotive, financial services, travel and hospitality, healthcare, life sciences, media and telecommunications.