Lead Data Engineer (Streaming & Real-Time Data Platform)

Banank PL sp. z o.o. is building the next-generation real-time data platform for a digital banking ecosystem, focusing on streaming data systems for backend services, business intelligence, operational decision-making, and AI-driven analytics.

• 6+ years of experience in Data Engineering with a strong focus on streaming and real-time platforms.
• Proven experience designing enterprise data platforms for operational backend systems.
• Strong understanding of modern data architecture, including real-time processing, lakehouse concepts, and distributed data systems.
• Hands-on experience with streaming data platforms and distributed analytical query engines.
• Strong understanding of event-driven architectures and streaming consistency models.
• Experience designing high-throughput, low-latency distributed systems.
• Experience implementing pipelines as code, automated deployment, and version-controlled data infrastructure.
• Desirable experience building Customer 360 or similar enterprise customer data models.
• Experience building cloud-native enterprise data platforms.
• Strong programming skills in Java, Python, or similar.
• Strong written and spoken English.
• Legal right to work in the EU; candidates from CIS countries may be considered under contractor engagement.
• Ability to work effectively in a fully remote environment.

• Own the architecture and long-term evolution of Banank's enterprise data platform.
• Define scalable architectural principles for operational, analytical, and real-time data systems.
• Design reusable enterprise data models and data products supporting backend services, business intelligence, regulatory reporting, and AI applications.
• Ensure enterprise data remains consistent, governed, discoverable, and reusable across the organization.
• Design and implement low-latency streaming pipelines supporting operational banking workloads.
• Build pipelines as code, ensuring fully automated, version-controlled, and reproducible infrastructure.
• Enable backend services to consume real-time streams.
• Implement and operate streaming-first data platforms and distributed analytical query engines.
• Design modern data lakehouse architectures supporting both streaming and batch workloads.
• Build scalable serving layers capable of supporting operational APIs, business intelligence, and advanced analytics.
• Design data models supporting semantic querying and natural language interaction with enterprise data.
• Ensure the data platform is AI-ready and capable of supporting future intelligent automation and decision-support solutions.
• Establish enterprise-wide standards for data quality, monitoring, lineage, validation, and governance.
• Optimize latency, throughput, scalability, and resource utilization.
• Mentor Data Engineers and promote engineering excellence.
• Define engineering standards, architectural guidelines, and best practices.

Must have the legal right to work in the EU; candidates from CIS countries may be considered under a contractor engagement model.