Related skills
azure aws gcp databricks apache spark📋 Description
- Lead agile delivery team across data & analytics lifecycle on cloud projects.
- Identify technologies and architect scalable data platforms using cloud services.
- Guide architectural decisions across data engineering: data lakes, ingestion pipelines, processing.
- Enable advanced analytics and AI-driven solutions to unlock client value from data.
- Design data platforms enabling ML/AI with governance.
🎯 Requirements
- Lead across data engineering lifecycle on large, complex, scalable platforms.
- Engineer big data patterns and solve complex data challenges.
- Design scalable data platforms including data lakes and ingestion pipelines.
- Engineer and model best practices for RDMS and NoSQL databases.
- Design distributed processing using Spark (Databricks) and BigQuery or similar.
- Design cloud-based solutions (AWS, Azure, GCP) and cloud-native patterns.
🎁 Benefits
- People-first culture with open communication and knowledge sharing.
- Growth through challenging projects and learning events such as Lunch & Learns.
- Community groups (football, gaming, yoga) for wellbeing.
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