Analytics Engineer: ML Ops, Data Pipelines & Azure

Bupa Australia; Melbourne; Presencial; AUD 120.000 - 150.000; Jornada completa

Descripción de la vacante

Bupa Australia is seeking an Analytics Engineer to deliver and productionise data science and analytics projects, aligning with the analytics roadmap and the Azure-based data platform migration. You will collaborate across data program teams to deploy ML-enabled insights and customer analytics solutions that drive better health outcomes.

In this role you’ll engineer data pipelines, feature stores, and dashboards using SQL, Python, Azure services, and Power BI, with an emphasis on scalable,

Formación

• 3+ years in customer analytics / data science / data engineering or similar field.
• Engineering using cloud-first approaches.
• Experience with data processing frameworks and modern data management practices.
• Familiarity with Agile working rhythms.
• Proficiency in SQL; Python preferred.
• Experience with cloud data services (Azure preferred).

Responsabilidades

• Understand detailed data requirements with stakeholders and translate into data-driven solutions.
• Engineer data pipelines from acquisition to consumption (reports, dashboards, models, APIs).
• Develop reusable data features and utilize a feature store where appropriate.
• Monitor data quality and processes to minimise risk.
• Adhere to Bupa's design standards and guidelines.

Conocimientos

SQL/TSQL

Python

Azure data services

Azure Synapse

Azure Databricks

Azure ML

Power BI

Spark

Data pipelines

Herramientas

Azure Synapse

Azure Databricks

Azure ML

Power BI

Descripción del empleo

Bupa Australia is seeking an Analytics Engineer to deliver and productionise data science and analytics projects, aligning with the analytics roadmap and the Azure-based data platform migration. You will collaborate across data program teams to deploy ML-enabled insights and customer analytics solutions that drive better health outcomes.

In this role you’ll engineer data pipelines, feature stores, and dashboards using SQL, Python, Azure services, and Power BI, with an emphasis on scalable,