Human Resources Data Engineer

at  RIO Tinto

HR DATA ENGINEER

• Tremendous opportunity to join a global organisation at the forefront of mining
• Great work life balance and attractive benefits
• Be part of a group that is safety focused and values inclusion
• 12-month fixed term or secondment position that can be based in Brisbane or Perth (Australia), Montreal (Quebec), Delhi (India), or Ulaanbaatar (Mongolia)
• This recruitment process will require a technical assessment or GitHub portfolio in addition to an interview

Finding better ways to provide the materials the world needs.
We are looking for a HR Data Engineer to join a global team of technology experts and engineers in this exciting new field where Data Science and Business Intelligence meets Human Resources and Psychology of the workplace.
This is a great opportunity for a Data Engineer with an interest in the cross section of data and people. The insights from our team have direct impact on strategic people-related decisions from recruitment processes and retention strategies to employee wellbeing and engagement.

Reporting to the Data Management Programme Lead, you will support the global business to design and continually improve services, solving business problems and providing insight to making improvements through:

• Designing, building, deploying and scaling data pipelines to serve machine learning and predictive models
• Data modelling and architecting data sets from different enterprise systems
• Engineering complex systems to manage big data compute tasks
• Challenging and collaborating to derive new and novel techniques to improve the service of data to models
• Developing platforms and processes that support the reproducibility of results
• ETL reporting from traditional and legacy systems.
• Ensuring best in class processes and techniques to develop and deploy data analytics solutions to the business
• Ensuring the quality assurance and quality control of all data analytics products released to the business
• Capturing and recording the intellectual property generated.
• Sharing what has been developed in GitHub to help foster a new generation of data driven decision makers and enable them to improve upon what has already been done
• Engaging with clients and key stakeholders to build their understanding of data analytics
• Providing training and knowledge transferring to support the deployment and continuity of the analytics products developed