Location: Krakow, Poland
Experience: 10 Years
Language: English
Salary: Best in Market
Requirement:
• Software design, Scala, Spark & Hadoop development, automated testing of new and existing components in an Agile, DevOps and dynamic environment
• Promoting development standards, code reviews, knowledge sharing
Product and feature design, scrum story writing
• Data Engineering
• Product support & troubleshooting
• Implement the tools and processes, handling performance, scale, availability, accuracy and monitoring
• Liaison with BAs to ensure that requirements are correctly interpreted and implemented. Liaison with Testers to ensure that they understand how requirements have been implemented – so that they can be effectively tested.
• Participation in regular planning and status meetings. Input to the development process – through the involvement in Sprint reviews and retrospectives. Input into system architecture and design.
Responsibility:
• Communication skills (data). You know how to communicate to and between technical and non-technical stakeholders as well as facilitate discussions within a multidisciplinary team, with potentially difficult dynamics. You can advocate for the team externally. You know how to manage different perspectives.
• Data analysis and synthesis. You know how to undertake data profiling and source system analysis and can present clear insights to colleagues to support the end use of the data
• Data development process. You can design, build and test data products that are complex or large-scale. You know how to build teams to complete data integration services
• Data innovation. You understand the impact of emerging trends on the organisation in data tools, analysis techniques and data usage.
• Data integration design. You know how to select and implement the appropriate technologies to deliver resilient, scalable and future-proofed data solutions.
• Data modelling. You understand the concepts and principles of data modelling and can produce relevant data models across multiple subject areas. You know how to reverse-engineer data models from a live system. You understand industry-recognised data modelling patterns and standards and when to apply them. You can compare and align different data models