- Position: Cloud Data Architect
- Location: Kraków, Poland
- Working mode: Initially remote; once the Kraków office is ready, 3-4 days per week onsite
About our client
Our client is an Israeli sports-tech company combining advanced data engineering, AI/ML and mathematical modelling to build high-performance real-time sports analytics solutions. The company processes large volumes of real-time data across sports including football, basketball, baseball and American football, turning it into predictions and actionable insights. Its solutions are designed for sports organizations, leagues, broadcasters and other data-driven businesses. The company is now building its new R&D team in Kraków, creating the opportunity to join the organization at an early stage and have a direct impact on its technology and infrastructure.
The Role
As a Cloud Data Architect, you will take ownership of cloud infrastructure, real-time data processing and the architecture required to support a high-concurrency platform handling millions of users and hundreds of thousands of commands per minute. You will work at the intersection of cloud engineering and data architecture, designing scalable, low-latency and highly available systems. The role combines hands-on technical work with architectural decision-making, performance optimization and collaboration across teams. You will also contribute to the long-term evolution of the platform, including scalability, cost optimization, observability and disaster recovery.
Key Responsibilities
- Design, deploy and maintain scalable cloud environments using Infrastructure as Code.
- Build and operate real-time, event-driven data pipelines designed for high throughput, fault tolerance and low latency.
- Design and optimize data storage and data lake solutions supporting both transactional and analytical workloads.
- Develop highly available networking, API gateways, automated failover mechanisms and zero-downtime routing strategies.
- Integrate data validation, monitoring and observability into the data pipeline lifecycle.
- Identify and resolve performance bottlenecks and data quality or data drift issues.
- Drive long-term cloud scalability, cost optimization, disaster recovery and system benchmarking.
- Work closely with engineering and data teams to translate business and technical requirements into scalable architecture.
What We’re Looking For
- 5+ years of experience in Cloud Infrastructure, Data Engineering or Distributed Systems Architecture.
- Strong experience designing and provisioning infrastructure with Terraform.
- Hands-on experience with Docker and Kubernetes.
- Experience with cloud platforms, particularly AWS; GCP experience is also relevant.
- Strong knowledge of distributed, event-driven data architectures, particularly Apache Kafka and Change Data Capture (CDC).
- Experience with object storage such as S3, data lakes and relational and NoSQL/document databases.
- Strong programming and scripting skills in Python and Bash; experience with Java or Kotlin is a plus.
- Experience designing and optimizing ETL/data pipelines and working with high-volume data processing.
- Ability to combine high-level architecture with hands-on performance tuning and implementation.
- Strong English communication skills (C1); Polish is not required.
- Background in fintech, iGaming or other high-throughput platforms is a nice-to-have.
What We Offer
- Opportunity to join a new R&D organization in Kraków and influence its technical foundations from the beginning.
- Primarily employment based on an employment contract (UoP), with B2B cooperation also planned as an option later.
- Initially fully remote work, followed by a hybrid model with 3-4 days per week from the Kraków office once the office is ready.
- Opportunity to work on large-scale, real-time data infrastructure serving millions of users.
- International environment and direct collaboration with the company’s leadership and technical teams.
- Competitive compensation and equipment necessary to perform the role.
- The opportunity to work on complex cloud, data engineering and distributed systems challenges with a strong focus on scalability and performance.
