Senior Analytics Engineer

nXscale provides flexible outsourcing solutions for startups and scaleups. We partner with global companies to help them build teams and scale operations.

Whether you're at home or on your way to work, you're probably reading this because you're looking for a new experience or a new challenge. Our client has assembled a group of seasoned superannuation and financial services professionals. Bringing together exceptional brains from Administration, Product, and Technology positions us to develop novel solutions to decades-old challenges.

What you will do:

● Collaborate with team members to collect business requirements, define successful analytics outcomes, design data models and deliver outcomes that solve the business needs ● Provide clean and appropriate data sets/views to enable data and reporting requirements to be solved ● Provide insights and workshop with Data Engineers the gaps of data in the data lake for data engineers to pipeline in ● Build data transformation scripts leveraging dimensional modeling techniques ● Incorporate tests in the transformation scripts and mappings of data sets as the shape changes from source to target systems ● Continuous improvement activities on performance optimisation of all data pipelines and data stores, applying engineering best practices to code ie Versioning, automated testing, CI/CD ● Provide input into the discovery and solution phase for Business/Client needs, assessing risk in exposing data and working inline with GROW’s risk framework ● Contribute to business cases the Head of Data Engineering will be putting forward to GROW’s Strategic Leadership Team ● Support the Product owner in communicating and documenting the delivery and handover of a report to the relevant internal/external stakeholders ● Proactively own development as a leader and specialist including the development of future leaders within the function ● Role model a commitment to continually evolving our risk culture as a differentiator for our people and clients

Who you are:

● Proficiency in SQL and at least one programming language (e.g., Python, Scala) ● Experience with data modeling and ETL processes ● Familiarity with cloud-based data platforms (e.g., AWS, Azure, GCP) ● Knowledge of data integration patterns and best practices ● Experience in planning and executing data migration projects ● Understanding of data quality assurance and validation techniques ● Ability to design and implement data reconciliation processes ● Familiarity with various database systems (e.g., relational, NoSQL, data warehouses) ● Understanding of API integrations and data interchange formats (e.g., JSON, XML)