Have a important say on the data architecture and future roadmap Data for good and help improve health outcomes Remote and Work from Home role (can be based anywhere in Australia) Experience in handling imaging or computer vision related datasets is essential (experience with tabular data only won’t cut it unfortunately) Help medical professionals and doctors by substantially improving patient diagnosis accuracy. Who ended up becoming what they always wanted to be back when they were at school? You probably don’t know that many people that did. There’s nothing wrong with this, perhaps it’s just how life played out. But the few such people that you do know that did it, may actually be quite happy about it all. There is a group of people that are trying to increase such happiness, helping people to live longer and healthier. They came up with a great idea from academic research a decade ago and have started to commercialise these great ideas 3 years ago. If you've always wanted to be a Data Engineer, keep reading. Think of a accurate diagnostic imaging infrastructure that helps doctors and medical professionals diagnose illnesses more accurately, then putting these findings into tangible medical device products that can be rapidly scaled, commoditized and widely used in clinics and hospitals all over the globe. Essentially helping people live longer and healthier. The Engineering team (24) has been gradually built up since 2021 and they’re in the early stages of adding their Data capability into the business. Purpose of the role is to help them set up their data systems and architecture which is still in its infancy. Their Data Infrastructure is reasonably new and there’s an opportunity to shape its architecture, its scalability and advise on the future roadmap. They are investigating the impending move from on-prem to a hybrid cloud approach, incorporating machine learning frameworks (e.g. TensorFlow, Pytorch), cloud and distributed storage tech (e.g. Terraform, IAAC, Hadoop, Spark), doing a bunch of scraping of data, pulling data from APIs, and using it within their apps. They are looking to create a more scalable data engineering process. Key words aren't too important for this role, rather they're looking for someone who's worked with "unstructured data" and can advise on best practices and take their Data Infrastructure to a more mature level. Due to the complexity of the projects, you’ll need to have experience in handling imaging or computer vision related data (tabular data won’t cut it unfortunately). If you’ve worked on projects where you’re handling high volumes of data that’s related to CNNs, object detection, image processing or similar (e.g. identifying anomalies from high definition images), asset inspection (e.g. fault finding in assets such as pipes, railway tracks etc.), autonomous vehicles (collision avoidance, automated mining / rail tech), that’s the sort of experience we’re looking for. You’ll be au fait with doing a full audit and architecting how to set up for the future. Classic Python and on-prem infra is set up currently and they’re investigating which cloud provider (e.g. AWS, Azure, GCP) to use one day. You’ll be a core contributor in landing on data architecture and infrastructure for the future. Start-up / Scaleup experience is not essential, but the mindset of getting in and having a go yourself and owning your lane is critical. MCS Consulting has been a trusted Recruitment advocate for over 25 years to many companies in high value Manufacturing, Finance, R&D, IT&T and Government. We have an effective personal and honest approach that really makes the difference. www.mcs-consulting.com.au We are more than happy to discuss career aspirations. At MCS we are here to help, not just recruit