You'll be busy, working closely with the business teams from data scientists and analytics professionals to Marketing and Product Strategy for this large financial services company.
You will ork closely with Product Data Scientists to develop working software which delivers the desired business outcome and play a key role in familiarising the extended team in data engineering tools and best practices
Skills and Experience
‘ Experience in developing and data engineering with Python, Azure and/or AWS, Spark/Hive/Hadoop
Understands the principles and needs of Data Scientists and how data requirements differ from regular reporting
Good knowledge of the Linux environment
Proficiency in building complex data pipelines/ETL/ELT scripts
High level of organisational skills to sustain momentum in multiple work-streams
Understands the principles and best practices of data modelling, interface design, code development, and testing, and you can apply these principles in real-world dev environments.
Knowledge and experience of contributing to the development of technology solutions, both in house developed bespoke applications and commercially available off the shelf solutions, especially for analytical work.
Familiarity with Agile delivery methodologies, (SAFe is preferred)
‘ Experience of SQL Server; data modelling, warehousing and SSIS
Knowledge and experience of data visualisation tooling, preferably Tableau Server and Tableau Desktop
Knowledge in unit testing framework (NUnit, Jest, Enzyme, Jasmine, Karma) and mocking frameworks.
AWS or Azure certification
McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.
