Data Engineer

• An appreciation for data engineering or software development.
• A strong conceptual and analytical mindset, with the ability to think in an abstract context and articulate, explain and sell ideas and approaches to other stakeholders.
• Fluency in Python and familiarity with other programming languages.
• Skills with SQL and probably other query languages.
• Some exposure to PySpark and/or other common Python packages such as Pandas or NumPy.
• An understanding of batch processing pipelines and testing / monitoring systems.
• Bachelors, masters or PhD qualifications in a relevant technological or engineering field.

Other skills and interests are beneficial but not essential, including in machine learning and AI, leadership and mentoring, Scala, Spark, Elasticsearch, Datadog, Databricks, AWS, Docker / Kubernetes.