Job Description
Condor – passion is our compass! And that's more than just a claim, it's our DNA: As Germany's most popular vacation airline, we take our guests to the world's most beautiful vacation destinations. Every year, over nine million passengers fly with Condor aboard our more than 50 aircraft to around 90 destinations in Europe, Africa and North America. From the fall of 2022, Condor will be the German launch customer for new long-haul Airbus A330neo aircraft of the latest generation, which, thanks to state-of-the-art technology, is the European leader in fuel consumption of 2.1 liters per passenger per 100 kilometers while offering the highest level of customer comfort. Our more than 4,000 employees on the ground and in the air give their best every day with passion, dedication and know-how and are writing the next chapters in our 66-year history. We are ready for take-off! Are you too? Become part of the Condor family now and apply for a job with us!
Data Architect (all genders)
- Architecture Design: Develop and maintain scalable, cloud-native data architectures that support analytics, real-time workloads, and operational integrations across Condor's data platform
- Infrastructure Engineering: Define and evolve foundational infrastructure patterns (e.g., modular data layers, CI/CD pipelines, observability, testing frameworks) in close partnership with data engineering
- Modelling & Semantics: Own enterprise data modeling — relational, dimensional, and semantic — ensuring models are reusable, performant and aligned with governance and business logic
- Standardization: Establish technical standards for lineage tracking, metadata, version control, and documentation to support transparency, reproducibility and team onboarding
- Tooling Strategy: Evaluate and recommend tools (e.g., dbt, Terraform, Airflow, Azure Synapse, Snowflake) that accelerate engineering productivity and platform scalability
- Cross-functional Enablement: Partner with engineers, analytics teams, and architects to embed architectural patterns into team workflows and drive a shared culture of technical excellence
- Scalability Planning: Proactively design for scale — across data volume, complexity, and user base — ensuring performance, reliability and extensibility as data demands grow
- Experience: 7+ years in data architecture or engineering roles, with demonstrated success in designing scalable cloud-native data platforms in Azure, AWS, or GCP
- Cloud Infrastructure: Deep hands-on-experience with Azure Data Services (e.g., Data Factory, Synapse, ADLS), Terraform or similar IaC tools and orchestration frameworks (e.g., Airflow)
- Modelling Expertise: Mastery of data modeling techniques — normalized, star / snowflake schemas, semantic layers — and their application to analytics and operational needs
- CI/CD for Data: Strong understanding of engineering workflows — Git-based version control, CI/CD for pipelines, testing strategies, and data release automation
- Tool Proficiency: Proficient with SQL and tools like dbt, Power BI, or LookML; able to design systems that bridge backend performance with front-end usability
- Governance & Security: Solid grasp of governance frameworks (data access, lineage, PII management), especially in regulated or complex data environments
- Collaboration & Influence: Skilled at working across teams to align architecture decisions with delivery realities — able to influence both engineering teams and executive stakeholders
- Languages: Business-fluent English skills and a good command of German both written and spoken
- Atmosphere – through a friendly and motivated team and flat hierarchies
- Excitement – through an interesting and varied job in a fascinating industry
- Further development – through competent induction as well as training and development opportunities
- Benefits – through attractive travel discounts and social benefits in addition to industry-standard compensation