Data Architect

Requirements:

• Proven experience acting as Solution / Data Architect in enterprise environments.
• Ability to take full ownership of architectural decisions.
• 5+ years overall experience in Data Engineering / Data Platforms.
• 3+ years hands-on architecture experience with Azure Databricks.
• Deep hands-on expertise in Databricks (cluster strategy, performance optimization, Delta Lake design), Spark internals & performance tuning, Data Lake architecture (Bronze/Silver/Gold patterns).
• Proven experience designing and delivering enterprise-scale data platforms in Azure.
• Experience in legacy system modernization, migration or transformation programs.
• Experience working in the banking sector, with a focus on credit scoring.
• Understanding of regulatory and compliance constraints (e.g., data governance, auditability, security).
• English language skills (B2+ minimum, C1 preferred).
• Strong German language skills (B2+ minimum, C1 preferred).
• Experience in direct client-facing roles (workshops, architecture discussions, stakeholder alignment).

Nice to Have:

• Experience in Credit Bureau environments.
• Availability for business travel to client locations in Germany.
• European Union citizenship.
• Hands-on experience with Credit Scoring / Credit Scoring Services.
• Experience working with SAS (migration or integration).
• Experience in highly regulated financial environments (BaFin context).

,[Collaborate with business leaders to translate strategic objectives into actionable data initiatives., Evaluate business processes and identify opportunities for data-enabled optimization., Design and lead enterprise-scale solutions based on Azure Databricks., Architect and implement migration / transformation of legacy data platforms., Automate legacy systems and modernize data processing landscapes., Facilitate workshops and sessions to align technical solutions with business needs., Translate business requirements (e.g., credit risk, scoring, reporting) into scalable data solutions.] Requirements: Azure, Data, Databricks, SAS