Software Developer responsible for designing and implementing scalable data lifecycle solutions for ZEISS. Collaborating with digital partners and business units for seamless data governance and analytics.
Responsibilities
Design, implement and operate scalable data lifecycle solutions for data consolidation, processing and governance (batch & streaming)
Build and automate data transformation pipelines on the Azure Data Platform
Take end-to-end ownership of data applications, from conception and prototyping to production and stable operations
Drive architecture and technology decisions, including DevOps / DataOps processes and modern data platform patterns
Ensure high quality, performance, reusability and reliability of data solutions through clean-code and test-driven development
Collaborate closely with ZEISS business units and ZEISS Digital Partners, translating user needs into user-centric technical solutions
Support software releases, monitoring and continuous improvement in enterprise-scale environments
Requirements
3+ years of professional experience in software or data engineering
Strong programming skills in Python and/or Java
Experience with distributed data processing (e.g. Spark, Databricks or similar technologies)
Hands-on experience with Azure-based data platforms
Solid understanding of data pipelines, orchestration and data quality concepts
Experience with API-based integrations and distributed systems
Fluency in English
Experience with DevOps / DataOps, CI/CD and infrastructure-as-code
Knowledge of containerization and cloud-native architectures (e.g. Docker, Kubernetes)
Familiarity with data governance, metadata management and data sharing concepts
Experience with monitoring and logging tools (e.g. Grafana, Datadog)
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