A FEW OTHER THINGS WE WANT TO LET YOU KNOW ABOUT…

• carsales is an equal opportunity employer who prides themselves on fostering a diverse and inclusive workplace. We encourage everyone of all ages, genders and backgrounds to apply. If you’re a candidate with a disability or you’ll need some adjustments to be at your best, let us know how we can provide you with additional support.
• We know how important keeping that balance between work/life is and have a range of flexible working options on offer, including part time. We are open to this conversation during our recruitment process if you want to know more just ask!
• We are a proud Circle Back Initiative Employer which means we are committed to responding to every job applicant.
• Successful candidates joining the carsales family are required to undergo a National Police Record check and must have full-time Australian working rights on an ongoing basis.

WHAT YOU’LL DO

• Contributing to the delivery of scalable data architectures, and data product development & design best practices
• Leading collaborations across data disciplines to develop, optimise and maintain data pipelines and solutions
• Engages actively in facilitating team-based problem-solving sessions and contribute to the development of best practices
• Initiating and nurturing effective working relationships, acting as a trusted advisor on product analytics and commercial data solutions
• Leading technical recommendations and decision-making while, mentoring early-career engineers playing a key role in growing the team’s capabilities
• Owning the delivery of their allocated initiatives within specified scope, times and budgets

Critical to success in the role is the ability to operate in the liminal space between business, data and technical practice.

• An all-of-business mindset over siloed success; leading with high levels of personal integrity and accountability
• Skilled at distilling business and analytics requirements into well-defined engineering problems
• Skilled at applying appropriate software engineering methods (e.g. modularisations, abstractions) that make data assets tractable
• Track record architecting, building and integrating with RESTful APIs and microservices architectures
• Proficient in containerisation platforms (e.g. Docker) and CI/CD pipelines
• Data engineering experience (e.g. transformations, modelling) grounded in the basics of an analytical discipline
• Skilled in designing and building software/pipelines using cloud services such as AWS EC2, Glue, Lambda, SNS, SQS, IAM, ECS or equivalent
• Demonstrated experience with distributed technologies and data-intensive processing frameworks -e.g. Airflow, HDFS, Spark, EMR
• Proficient in at least two programming languages (e.g. Python, Spark, Scala). Experience with .Net frameworks highly favourabl