Cloud Data Engineer (Software | IoT)

Company Description

iLoF is working to enable a new era of personalized medicine, by using AI and photonics to build a cloud-based library of diseases biomarkers and biological profiles.

It is providing screening and stratification tools in an affordable, fast, portable way, saving up to 40% of cost and 70% of the time spent screening for clinical trials.

Supported by leading institutions like Microsoft Ventures, Mayfield or the Oxford University, iLoF is currently focusing a validated platform technology in one of the biggest epidemics of our times: Alzheimer's, while maintaining ongoing verticals on Digestive Cancer, Stroke and Infectious diseases. 

Job Description

Cloud Data Engineer (Software | IoT )

  • Experience in designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of Azure/GCP/AWS data and analytics services (preference for Azure)
  • Hands-on experience analyzing, re-architecting and re-platforming on-premise data warehouses to data platforms on Azure/GCP/AWS cloud (preference for Azure)
  • Experience in designing and building production data pipelines from ingestion to consumption within a hybrid big data architecture (preference for Azure)
  • Previous experience in architecting and implementing next generation data and analytics platforms on Azure/GCP/AWS cloud (preference for Azure)
  • Previous experience in Architecting and implementing data governance and security for data platforms
  • Previous experience in Machine Learning pipelines automation and model governance
  • Perform hands on management of cloud infrastructure
  • Knowledge in machine learning algorithms 
  • Identify automation opportunities and implement using tools 
  • Realize, terraform, cloud formation templates, and other similar tools
  • Work with Projects to help them adopt cloud infrastructure and services to reduce cost and deployment times
  • Experience with both relational and non-relational databases
  • Open-minded, Hands-on attitude and good command of English language


Responsibilities:

  • Integrate massive datasets from multiple data sources for data modelling
  • Implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production
  • Construction of cloud-based servers
  • Managing data transfer to cloud based system
  • Designing pipelines and architectures for data processing
  • Analyze in-house systems for potential migration to the cloud, creating production and migration schedules
  • Work with data science team to efficiently use cloud infrastructure to analyze data, build models, and generate reports/visualizations
  • Querying datasets, visualizing query results and creating reports
  • Ensure databases, datasets and cloud infrastructure are secure and comply with security regulations
  • Integrate ML pipelines into databases


Qualifications

Background:

  • Computer Engineering / Informatics/Computer Science
  • Biomedical or Electrical Engineering


Additional Information

Benefits & perks:

  • Competitive compensation
  • Equity options
  • Fast career progression in a rapidly-scaling startup