• Successful candidate will have experience creating data pipelines, to provision data from a variety of sources using tools like Spark, Azure Data Factory and Kafka.
• You will be able to identify appropriate data processes, structures, and models to meet customer objectives and have experience performing data transformations that meet customer and organisational needs.
• Will be proficient at coding in languages such as Python, PySpark, Scala, and writing SQL (however, we are not looking for people to just write code.)
• The client encourages people with a curious mind, to bring their outside experience, listen to and challenge their peers, to get the best possible results. In a nutshell, they like people who ask 'why?' The best solutions come from teams comprised of people with diverse skills working together with mutual trust.
• A candidate's ability to work in teams, often remotely, is critical, which means knowing when to listen, and when to speak-up.

Technical skills:

• Databases, modelling, and data flows: Common relational, non-relational and spatial databases. Workflow and ETL/ELT tools and methods.
• Cloud: Azure, AWS or GCP. Docker, Kubernetes, helm, data lake storage
• Web application development: Python frameworks (Flask, FastAPI), basic HTML/CSS/JS, frontend frameworks (like Angular)
• Programming: Linux terminal (e.g. ssh, bash, cron), APIs, developer collaboration (e.g git, jira, confluence)
• Data Science/AI principles: Principles of machine learning. Model serving.
• Agile and DevOps: Kanban, scrum, CI/CD, test automation, monitoring, and alerting