Data Specialist jobs in Germany

Role Description: Data Architecture Strategy & Design: • Define and implement enterprise-wide data architecture strategies, ensuring scalability, performance, and security. • Develop data models, pipelines, and storage solutions that support structured, semi-structured, and unstructured data. • Ensure alignment between data architecture, analytics, AI/ML models, and business intelligence (BI) platforms. • Drive the adoption of data lakehouse, cloud data platforms (Azure Synapse, AWS Redshift, Google BigQuery), and distributed computing frameworks. • Work closely with data engineering and analytics teams to optimize data pipelines and transformations. Cloud & Big Data Ecosystem Integration: • Lead the design and implementation of cloud-based data solutions, ensuring seamless integration with enterprise applications. • Define best practices for data ingestion, ETL/ELT, and real-time data streaming (Kafka, Spark, Databricks, etc.). • Ensure interoperability between on-premise, hybrid, and multi-cloud data environments. • Optimize data storage, processing, and retrieval across cloud platforms, improving cost efficiency and performance. Data Governance & Compliance: • Implement data governance frameworks, ensuring compliance with GDPR, HIPAA, ISO 27001, and other regulatory standards. • Define metadata management, data lineage, and data cataloging best practices. • Work with security teams to enforce data access controls, encryption, and role-based access management (RBAC). • Ensure data quality and integrity across the organization’s analytical and AI platforms. Data Integration & Interoperability: • Develop and maintain enterprise data integration frameworks, enabling smooth data exchange between systems. • Lead API-driven data integrations, event-driven architectures, and message queues for real-time data movement. • Establish data fabric and data mesh approaches, enabling a scalable, decentralized data ecosystem. • Work closely with business units, AI teams, and application developers to provide accessible, high-quality data. AI & Advanced Analytics Enablement: • Support AI and ML model development by ensuring high-quality data availability. • Define data architecture principles that optimize AI pipelines and feature engineering processes. • Work with AI engineers to deploy and operationalize AI models in cloud and edge environments. • Ensure efficient data versioning, feature stores, and reproducibility frameworks for AI workflows. Leadership & Team Development: • Lead a team of data architects, data modelers, and data integration specialists. • Foster a culture of data-driven decision-making and continuous learning. • Develop training programs and best practices for data architecture governance, performance optimization, and security. • Collaborate with cross-functional teams, including Data Science, Engineering, and Business Intelligence teams.

• Bachelor’s or master’s degree in computer science, Data Engineering, or related field. • 10+ years of experience in data architecture, big data engineering, or cloud data solutions. • Proven expertise in Azure, AWS, and/or Google Cloud-based data ecosystems (with certifications, Azure required). • Experience with data modeling tools, metadata management, and data governance platforms. • Strong understanding of data mesh, data fabric, and decentralized data architectures. • Background in leading and managing data architecture teams in enterprise environments. • Familiarity with BI/analytics tools such as Power BI, Tableau, or Looker. • Experience in supporting AI/ML workflows with structured, high-quality data pipelines