IBM DevOps Data Engineer in New York, New York
The shift toward the consumption of IT as a service, i.e., the cloud, is one of the most important changes to happen to our industry in decades. At IBM, we are driven to shift our technology to an as-a-service model and to help our clients transform themselves to take full advantage of the cloud. With industry leadership in analytics, security, commerce, and cognitive computing and with unmatched hardware and software design and industrial research capabilities, no other company is as well positioned to address the full opportunity of cloud computing. We are looking for a Data Engineer to join our Cloud Innovation Lab team in Austin, TX or Littleton, MA who innovates & shares our passion for winning in the cloud marketplace. The Cloud Innovation Lab is a team dedicated to ensuring that the IBM Cloud is at the forefront of cloud technology, from data center design to network architecture to storage and compute clusters to flexible infrastructure services. We are building IBM's next generation cloud platform to deliver performance and predictability for our customers' most demanding workloads, at global scale and with leadership efficiency, resiliency and security. It is an exciting time, and as a team we are driven by this incredible opportunity to thrill our clients. The Data Engineer will enable a data-powered intelligence within the continuous delivery and automation of IBM’s revolutionary new cloud infrastructure.
At least 8 years of relevant work experience
Demonstrable development experience in Python and common data engineering frameworks, including Pandas, Numpy, Scipy, Scikit-learn, Tensorflow, Matplotlib, PySpark, etc.
Experience programming R and supporting frameworks and applications, including GGplot, Shiny, etc.
Expertise with containerization technologies, including LXC, Docker, CoreOS, etc.
Deep understanding of relational (Oracle, MySQL), graph (Neo4j) and NoSQL (Cassandra, Mongo, etc.) databases.
Deep experience with designing and building dynamic, functional cloud-based data infrastructures.