Big Data Engineer Python
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Big Data Engineer
This role focuses on developing, integrating, and optimising large-scale data flows. It involves close collaboration with data scientists to translate analytical models into practical technical solutions, requiring hands-on expertise in data cleansing, pipeline design, component orchestration, and modern data technologies such as Hadoop, Spark, and API development.
Mission & Responsibilities
- Technical Collaboration: work closely with data scientists to develop effective technical solutions
- Data Optimisation: perform data cleansing, preparation, and integration
- Pipeline Engineering: design and build robust data pipelines
- System Integration: manage component orchestration
- Large-Scale Data Processing: responsible for batch Spark ETL, including data wrangling, joining, and aggregation
Technical Competencies
- AI Ecosystems & Frameworks, including:
- Modern Data Stack (MDS)
- On-premises Data Lake technologies (Hadoop, Spark, Hive)
- Large-scale data processing (Spark)
- Orchestration tools (Apache Airflow)
- Containerisation (Docker / Kubernetes)
- Python programming
- Architecture & Integrations:
- API development
- Cloud architectures (AWS, Azure)
Experience with real-time architectures and event streaming infrastructure is advantageous.
Behavioural Competencies
- Collaboration: able to work closely and effectively with data scientists to translate complex analytical needs into functional technical solutions
- Analytical & Organised: precise and methodical approach to data cleansing, preparation, integration, and pipeline design
- Problem Solving: quick and efficient in addressing bottlenecks in data processing or orchestration errors
We require full-time availability (100%), although 80% availability will be considered.
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