Lead Data Engineer
at Bupa
Sydney, New South Wales, Australia -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 23 Apr, 2025 | Not Specified | 23 Jan, 2025 | 8 year(s) or above | Data Science,Python,Management Skills,Actuarial Science,Sql,It,Machine Learning,Data Transformation,Data Engineering | No | No |
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Description:
OPPORTUNITY SNAPSHOT:
An exciting, Permanent opportunity has become b for a Lead Data Engineer.
The Actuarial Transformation Program (ATP) aims to modernise actuarial modelling tools and systems, many of which are currently maintained through spreadsheets. As part of this transformation, we plan to procure the following tools and solutions; Forecast Modelling, Rate Submission Tool, Volatility Modelling Tool, Analysis of Change Tool, Actual vs. Expected Cashflow Tool, and BI Dashboard reporting optimisation with existing solution.
ABOUT US:
Bupa has a strategic goal of being the most customer-centric digital healthcare organisation, with the use of data as an explicit pillar of this strategy.
The program pillars include:
- A Customer-Centric Focus - Bupa aims to grow our data products, the data that people have access to and the utilisation of data as a strategic asset that drives our Connected Care, Core Modernisation, and other strategic change agents
- Data Access and Democratization - Ensuring everyone has access to and can understand the data Bupa holds; reducing barriers to entry and make the complex simple for people who want to leverage our data assets
- Support for Access - Help leaders in ensuring easy access to data for people that they work with
- Empowerment - Enabling business people to do their role as owners, stewards, and leaders.
- Delivery & Customer Value First - Treat data as an asset to create value for customers and remove barriers to achieving compliance, risk, or other barriers to value
Responsibilities:
- Bachelor’s degree in Business, Actuarial Science, IT, or a related field.
- 8+ years of experience in data engineering or data science, ideally within insurance or actuarial domains.
- Advanced skills in cloud-based data engineering (Azure Data Lake, Databricks), data transformation, and machine learning.
- Strong programming skills in SQL, Python, and experience with machine learning frameworks; Experience with actuarial forecasting and volatility modeming
- Strong communication and team management skills
REQUIREMENT SUMMARY
Min:8.0Max:13.0 year(s)
Information Technology/IT
Analytics & Business Intelligence
Software Engineering
Graduate
Business actuarial science it or a related field
Proficient
1
Sydney NSW, Australia