• Design, develop, and maintain scalable data pipelines using Databricks and Delta Lake • Build and manage transformations across bronze, silver, and gold layers • Optimize processing for performance, reliability, and cost • Integrate data from ERP, CRM, APIs, and other enterprise systems • Develop gold-layer datasets aligned to standardized business definitions • Translate business requirements into reusable data models • Ensure consistency of core metrics across reporting • Align Databricks outputs with Power BI semantic models • Implement automated data quality checks and validation rules • Build testable, production-ready pipelines • Support impact analysis using lineage tools • Participate in CI/CD and deployment processes • Monitor and optimize pipeline performance • Troubleshoot issues across environments • Ensure data consistency between dev, test, and prod • Support high-volume data workloads • Use AI-assisted tools for development (e.g., Copilot, Databricks Agents) (Preferred) • Explore AI agents for testing, lineage analysis, and optimization (Preferred) • Partner with BI and business teams • Support governance and cataloging efforts • Document data models and pipelines

• Lead architecture and design activities for data, analytics, and AI initiatives • Define end-to-end data platform architectures, including ingestion, storage, transformation, governance, and consumption layers • Develop target-state architectures, migration strategies, and modernization roadmaps • Conduct architecture assessments and provide recommendations aligned to business objectives • Collaborate with engineering teams to ensure successful implementation of architectural designs • Establish architecture standards, best practices, and reusable patterns • Design and implement modern cloud-based data architectures • Lead architecture efforts involving Snowflake, Databricks, and major cloud platforms (AWS, Azure, and/or Google Cloud) • Architect solutions leveraging data lakes, lakehouses, data warehouses, streaming platforms, and AI/ML services • Serve as a trusted advisor to client stakeholders, including technical leaders, architects, and business executives • Facilitate architecture workshops, discovery sessions, and strategy discussions • Translate business requirements into actionable technical architectures and implementation plans • Present architectural recommendations and executive-level findings to client audiences • Support sales pursuits through solution design, proposal development, and client presentations • Mentor architects and engineers across the organization

• Build and optimize real-time streaming pipelines to ensure efficient routing of voice and chat session data into enterprise data platforms • Integrate generative AI solutions with enterprise knowledge bases to ensure accurate and context-aware conversational agent performance • Maintain and configure low-latency databases to ensure secure and reliable storage of session states and operational metadata • Design system architectures and technical blueprints to ensure scalable, resilient, and high-performance solutions • Delegate and manage engineering tasks to ensure effective team productivity and capability development • Develop and execute testing processes to identify system issues and ensure quality and stability in deployed solutions • Collaborate with stakeholders to align requirements, manage expectations, and ensure successful project delivery • Oversee automated PII redaction workflows across voice and text streams to ensure full compliance with data privacy requirements prior to storage.

Role Description - Aufbau, Betrieb und Weiterentwicklung einer skalierbaren Datenplattform (Warehouse / Lake / Lakehouse) - Entwicklung und Wartung robuster ETL/ELT-Pipelines zur Integration unterschiedlichster Datenquellen - Sicherstellung von Datenqualität, Performance, Skalierbarkeit und Kostenoptimierung - Implementierung von Monitoring-, Governance- und Sicherheitskonzepten (inkl. DSGVO) - Enge Zusammenarbeit mit Analytics-, Product- und Engineering-Teams - Automatisierung von Datenprozessen sowie kontinuierliche Verbesserung bestehender Architekturen - Aktive Mitgestaltung der Datenstrategie und Evaluation neuer Technologien Qualifications - Mehrjährige Erfahrung im Data Engineering oder in einer vergleichbaren Rolle - Sehr gute Programmierkenntnisse in Python und SQL sowie saubere Engineering-Standards (Tests, CI/CD) - Fundiertes Verständnis moderner Datenarchitekturen und Datenmodellierung - Praxiserfahrung mit Cloud-Plattformen (AWS, GCP oder Azure) und gängigen Data-Tools (z. B. Airflow, dbt, Spark, Snowflake) - Hohes Qualitäts- und Ownership-Mindset für produktive Datenpipelines - Fähigkeit, technische Lösungen verständlich zu kommunizieren und Business-Anforderungen zu übersetzen - Teamplayer mit Interesse an Mentoring und kontinuierlicher Weiterentwicklung - Verhandlungssichere Englischkenntnisse (erforderlich); Deutschkenntnisse sind ein Plus Benefits - Attraktive, marktgerechte Vergütung - Flexibles Arbeitsmodell: Remote-first mit optionaler Präsenz im Büro - 30 Urlaubstage - Strukturiertes Onboarding mit persönlicher Begleitung durch das Recruiting-Team - Transparente Kommunikation durch wöchentliche 1:1s und regelmäßige All-Hands-Meetings - Zugang zu Corporate Benefits - Langfristige Perspektive in einer wachsenden Unternehmensgruppe