Senior Data Architect / Data Engineer

Xebia is a global AI-first, digital transformation, and engineering partner with over 25 years of experience and 5,000 professionals across 16 countries. They specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products. In the CEE region, they deliver modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, and others, working with technologies including AWS, Azure, GCP, Databricks, and Snowflake.

• 7+ years of experience in Data Engineering, Data Architecture, or related roles
• Strong hands-on expertise with Apache Druid
• Strong experience with Kafka and event-driven architectures
• Excellent knowledge of large-scale analytical data modeling
• Experience designing real-time or near real-time reporting platforms
• Strong expertise in SQL and MySQL
• Experience processing and analyzing billions of events
• Deep understanding of distributed data systems and performance optimization
• Ability to independently assess existing architectures and propose improvements
• Excellent communication skills and stakeholder management capabilities
• Experience with Apache Flink as well as streaming data pipelines and stream processing
• Fluent English (spoken and written)

Nice to have:

• Knowledge of data enrichment and dimensional modeling techniques
• Experience implementing scalable unique-count solutions (e.g., HyperLogLog or similar approaches)
• Exposure to cloud-based data platforms and modern analytics architectures
• Experience mentoring engineers and providing technical leadership
• Experience with ClickHouse
• Experience with modern lakehouse architectures, open table formats (e.g., Apache Iceberg), or data lakes
• Background in SaaS, martech, or customer engagement platforms

• Analyzing and assessing the current multi-store reporting architecture
• Designing a scalable, high-performance reporting solution for very large data volumes
• Defining data modeling strategies for analytics and reporting workloads
• Designing approaches for event enrichment using metadata from multiple sources
• Creating efficient solutions for computing unique counts and analytical aggregations at scale
• Providing architectural guidance around real-time and near real-time analytics
• Evaluating and recommending technologies, patterns, and trade-offs across the data platform
• Collaborating with engineering teams to implement the proposed architecture
• Supporting migration activities ensuring reporting consistency throughout the transition
• Driving best practices related to data quality, scalability, observability, and performance optimization
• Providing technical guidance and mentorship to engineering team members

Work from the European Union region and a work permit are required.