Data Architect with German

• Experience: Minimum 5+ years of hands-on experience as a Data Architect or Data Platform Architect.
• Cloud Stack: Deep expertise in AWS Data Analytics services, with proven focus on AWS Data Lake and EMR.
• Big Data & Orchestration: Strong background in Hadoop, Spark, and workflow orchestration with Apache Airflow.
• Certifications (Must-Have):
  • AWS Certified Data Analytics (Specialty) or AWS Certified Solutions Architect.
  • ITIL Foundation Certification.
• Languages: Fluent German (C1/C2 level or Native) is mandatory; fluent English for team collaboration.
• Track Record: At least 4 relevant project references over the past 8 years demonstrating major architectural capability areas.
• Methodology: Practical experience leading delivery in Agile/Scrum environments.

Nice to Have

• Experience with additional cloud data technologies (Snowflake, Databricks, Terraform).
• Experience in regulated industries or financial/enterprise sectors in the DACH region.

We are seeking an experienced Data Architect with fluent German to design, modernize, and scale enterprise data platforms in the cloud. In this role, you will lead the architecture of AWS-based data lakes, streaming solutions, and data pipelines for major clients in the DACH region. You will bridge technical engineering with strategic governance, ensuring scalable, secure, and high-performing data architectures.

,[Data Architecture & Design: Design and implement robust, scalable cloud data platform architectures leveraging the AWS Data Analytics stack (Data Lake, EMR, S3, Glue, Redshift)., Big Data & Pipeline Engineering: Architect high-throughput data processing pipelines utilizing Hadoop, Spark, and Apache Airflow., Automation & DevOps: Establish automated CI/CD deployment pipelines and infrastructure management for seamless data delivery., Data Governance & Security: Define and enforce standards for data classification, privacy, security, and lifecycle management across all environments., Migration & Integration: Lead complex end-to-end data migration initiatives from legacy/on-prem systems to modern AWS cloud environments., Stakeholder Engagement: Collaborate closely with business leaders, product managers, and engineering teams in an Agile/Scrum framework, using Jira, Confluence, and MS Teams.] Requirements: Data analytics, AWS, Data Lake, Hadoop, Spark, Cloud, Snowflake, Databricks