Summary
✨ AI‑Generated
Join a big data engineering team working with Scala, Java, Spark, and Azure. Build and operate data platforms using containerization, Kubernetes, Databricks, cloud storage, PostgreSQL, automated testing, security controls, monitoring, and infrastructure-as-code practices. The role follows a hybrid work model.
Highlights
Work on large-scale data engineering using Scala, Java, Spark, Azure, Kubernetes, and Databricks. The role spans cloud infrastructure, security, monitoring, testing, and infrastructure as code, with a hybrid work model.
Description
Location: Krakow, Poland (3 days hybrid)- Prefer hybrid working
Exp: 5-8+ years
Tech skills: Scala, Java, Spark, Shell, Azure, Sonar, docker hub, container registry, nexus, Postman, Azure CLI
• Programming Language: Scala, Java, Spark
• Tools: Gitlab, Sonar, docker hub, container registry, nexus, Postman, Azure CLI
• Build Scripting: Gradle, Maven, Shell
• Packaging Tool/Technology: Shell
• Cloud Technology: Azure
• Hosting: Experience with container management platforms like Kubernetes and databricks
• Data: Storage accounts, PostgreSQL, knowledge on Spark and Data Bricks API,
• Security: Azure AD (SAML Token based, Single sign-on), Hashi corp Vault, Managed Identities (Service Principals)
• Monitoring: Log Analytics, Azure Metrics, Azure Monitor,
• Infrastructure as Code (IaC): ARM
Test Automation:
• Test Frameworks: Cucumber, Junit, Mockito
• Tools: Gitlab, Sonar, docker hub, container registry, nexus, Postman
• Build Scripting: Maven, Shell
• Service / API Test: I want to test your endpoints as thoroughly as possible
• End to End Test: of the integrated system (continuous integration can be a major help here)
• Solid knowledge of QA methodologies, test planning, system dependencies, and product integration phases
Key Responsibilities
1.
End-to-End Project Ownership
• Gather requirements directly from business users
• Perform business analysis and data analysis
• Design system architecture
• Develop solutions
• Support testing and validation
• Work with DevOps team for deployment
• Provide ongoing support after release
2.
AI/GenAI Solution Development
• Build applications leveraging LLMs (e.g., OpenAI APIs)
• Implement use cases such as:
o Content summarisation
o Intelligent filtering and categorisation
• Evaluate when AI is appropriate vs traditional coding approaches
3.
Full Stack Development
• Work across the entire stack rather than specialised roles
• Handle:
o Backend logic
o Data processing
o Integration layers
• No separation into traditional roles (DB, UI, middleware)
4.
Architecture & Design Decision-Making
• Independently design and justify technical architecture
• Make decisions for greenfield projects
• Explain trade-offs and reasoning behind implementation choices
5.
Stakeholder Interaction
• Engage directly with:
o Business users
o Product owner
• Translate business needs into technical solutions
• Handle feedback and change requests directly
6.
Agile & Independent Working Model
• Work in a small pod (lean team)
• Handle projects independently with minimal supervision
• Participate in design discussions but own individual project delivery Technology Stack (Indicative)
• Primary Language: Python
• AI/ML: LLM integrations (OpenAI or similar)
• Data Platforms: Databricks, Delta Lake
• Cloud: Azure ecosystem
• Visualisation (optional): Power BI (not mandatory) Required Skills & Capabilities
Core Skills
• Strong full stack development capability
• Solid understanding of system architecture and design
• Experience building end-to-end applications
AI & Data Skills
• Experience working with GenAI / LLM-based solutions
• Ability to integrate AI into real-world use cases
