Beschreibung
Be a Part of Something BIG! Responsible for designing, building, and operating scalable data ingestion, transformation, and serving capabilities across a modern hybrid cloud data platform, ensuring solutions are reliable, secure, reusable, and aligned to enterprise architecture and governance standards. Develop and optimise batch and streaming pipelines using cloud tools such as Databricks and Kafka, applying sound engineering practices to ensure performance, resilience, and maintainability.
Contribute to the delivery of reliable, secure, and high-quality data for analytics, reporting, and machine learning use cases Lead the implementation and operationalisation of knowledge base and retrieval-augmented generation solution stacks to support scalable GenAI and agentic use cases across business domains Make an Impact by: Design, build, optimise, and maintain batch and streaming data ingestion pipelines using platforms such as Databricks and Kafka, ensuring scalability, reliability, observability, and alignment with enterprise data architecture standards. Perform data transformation and cleansing using PySpark or SQL based on business and technical requirements Monitor and troubleshoot data workflows to ensure data quality and pipeline reliability Provide technical guidance to engineers and delivery partners on data platform patterns, reusable components, code quality, deployment readiness, and production support practices. Lead integration of data from diverse source systems in
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