Purpose
Design new solution (standard and non-standard) to fulfill customer requirements. Execute testing and analyzes to identify flaws of the configuration. Create migration concepts and plans describing all necessary steps to deliver successful migration of new solution. Execute and support migrations/implementation of designed solution to deliver new functionality to the customer. Test, validate and document new releases in order to identify flaws and provide migration plan from old to new version of the release.
About team and project
We’re part of the Finance & B2B domain within the DATA TRIBE, driving the creation of a future-proof data warehouse landscape in the One Data Ecosystem (ODE). Our mission? To migrate our current data architecture to the Google Cloud Platform (GCP) — an ambitious, innovative, and rewarding challenge!
If you’re excited about working in a future-oriented, agile environment where learning and growth never stop, this is your opportunity. Bring your skills, curiosity, and drive — and together, we’ll shape the next generation of data solutions.
WHAT WILL YOU DO?
- Analyze data infrastructure: Review existing systems and documentation to assess the current state and identify areas for improvement.
- Design robust data solutions: Develop scalable, stable, and maintainable architectures that meet business needs.
- Translate requirements: Convert business and technical inputs into actionable technical specifications.
- Lead international collaboration: Coordinate with global expert teams to deliver comprehensive end-to-end data solutions.
- Plan migrations: Create and execute migration strategies for transitioning to new data architectures on GCP.
- Ensure quality through testing: Develop and run test cases for data pipelines, system integrations, and new solutions.
- Resolve complex issues: Investigate data-related problems, identify root causes, and implement effective solutions.
- Support presales and implementation: Provide technical consultation to guide decision-making and solution design.
- Document thoroughly: Prepare and maintain detailed technical documentation throughout the project lifecycle.
- Engage stakeholders: Collaborate with architects, data experts, production, and operations teams across domains and geographies.
- Communicate effectively: Utilize excellent German and good English skills, fostering strong teamwork and clear communication.
- Apply technical expertise: Leverage hands-on experience in data engineering, including ETL processes, data modeling, SQL, Python, UNIX, GIT, and UML.
- Analyze complex relationships: Identify and clearly present intricate connections with a proactive, goal-oriented mindset.
- Make informed decisions: Design and implement effective decision-making processes.
- Manage projects and requirements: Plan, implement, and oversee requirements throughout project lifecycles.
- Work agilely: Collaborate within interdisciplinary teams using agile methodologies.
- Model data effectively: Build scalable, stable, and maintainable data models.
- Conduct thorough testing: Perform module, interface, and system integration testing.
- Ensure data protection: Apply basic knowledge of data privacy, including attribute classification and pseudonymization/anonymization.