- Expertise in architectural design of analytics solutions, and experience in subsequent implementation of such solutions
- Experience in data collection techniques, data storage technologies for structured and unstructured data
- Experience with Big Data technologies, such as Hadoop, Hive, Spark, Cassandra
- Experience in designing, building, and deploying data pipelines
- Experience with ML environments such as Databricks, and how to use these for the development, versioning, deployment, and maintenance of ML models
- Experience integrating ML solutions and libraries into applications and products
- Knowledge of ML deployment tools such as Docker, Kubeflow, Kubernetes
- Experience with cloud service offerings from AWS, Azure or GCP
- Advanced critical thinking and problem-solving skills
- Advanced presentation and communication skills
- Ability to work as a team member in a fast-paced environment
Preferred:
- Knowledge of DataOps.
- Knowledge of data versioning tools such as git or DVC
- Experience working in Linux
- Experience with Agile software development processes is preferred
Roles & Responsibilities:
- Help define architectures that fulfil the organization’s data analytics strategy
- Play a key role in the definition of the architecture and design of both cloud-hosted and on-premises enterprise solutions, as well as edge analytics solutions
- Identify and implement analytic solutions involving cloud, open source, and AI technologies that enable end-to-end support of the entire analytics workflow and can be used to develop ML and AI models, incorporate those models into products, and allow for the deployment and maintenance of those models
- Work with Product Management, Services, customers, and data science experts to develop products that provide analytics solutions
- Work with application developers to develop analytics products that are deployed to end-users as part of packaged solutions
- Set up infrastructure for machine learning and model deployment
- Define a CI/CD framework to frequently deliver code/features to production
Generic Managerial Skills
- Strong diagnostic skills to analyze, track, trouble-shoot, and solve complex problems and design appropriate solutions
- Ability to prioritize and perform work independently, and to prioritize the work of others.
- Good interpersonal skills and ability to foster teamwork