Data Engineer, Stint

• Excellent problem-solving abilities demonstrated through academic or professional experience
• Strong foundations in data architecture, data engineering best practices, and scalable data solutions
• Solid understanding of data modeling techniques, database design, and data normalization
• Proficiency with Python and SQL, ideally with experience using data processing frameworks (e.g. Kafka, NoSQL, Airflow, Tensorflow, Spark)
• Willingness to develop basic to intermediate proficiency in backend development (e.g., Python with Django) to support data pipeline integrations
• Familiarity with data versioning and data quality management practices
• Familiarity with build and deployment automation and CI/CD (e.g. Jenkins, CircleCI)

Desirable

• You will be designing, building, and maintaining scalable data pipelines and architecture to support analytics that will feed live into our mobile and web-apps as well as enabling data-driven decision-making internally
• Reporting To: Jack Weeks
• You will be combining business analytics, data visualisation, data mining and data infrastructure to enrich data access across all business units and to enable data-driven decisions
• Building and maintaining scalable data pipelines to support data integration into our customer-facing mobile and web-apps as well as internal dashboards
• Designing and implementing data architecture to optimize data storage, retrieval, and processing
• Developing ETL processes to ingest, transform, and load data from various sources, specifically APIs
• Collaborating with data scientists and software engineers to understand data needs for our customer-facing mobile and web-apps
• Working with internal stakeholders (e.g., Head of Ops, Head of Commercial) to understand and shape data requirements for internal data-driven decision making
• Creating and maintaining data documentation, monitoring pipeline performance, and troubleshooting issues

• 1. Applied
• 2. Review
• 3. Interview
• 4. Hired