Position Purpose: The Data Platform Team looks to raise the level and productivity of data engineering and data science by building, scaling and supporting our big data infrastructure with an emphasis on simple and efficient solutions on top of complex distributed data stores. As a contributing platform engineer you will assist in architecting, designing and implementing a new, cutting edge, cloud platform expanding our data assets within scalable, elastic systems that can be instantiated on demand, on cloud.

• Create cloud and big data technical design recommendations for developing and integrating new software and system technologies – from the physical layer through to the virtual layer – per written specifications; test, evaluate, engineer, implement and support said technologies.
• Review, influence and contribute to new and evolving design, architecture, standards, and methods for operating and contributing to services within our big data ecosystem.
• Add to our existing business and data models. Reviews existing designs and processes to highlight more efficient ways to complete existing workload more effectively through industry perspectives.
• Drive technical innovation and efficiency in infrastructure operations through automation by assisting in improvements to continuous integration, continuous deployment and monitoring
• Create cloud and big data technical design recommendations for developing and integrating new software and system technologies – from the physical layer through to the virtual layer – per written specifications; test, evaluate, engineer, implement and support those technologies
• Collaborates with technical teams and utilizes system expertise to deliver technical solutions, continuously learning and evolving big data skillsets.
• Monitors and evaluates overall strategic data infrastructure; tracks system efficiency and reliability; identifies and recommends efficiency improvements and mitigates operational vulnerabilities. Respond to and resolve emergent service problems. Design solutions using automation and self-repair rather than relying on alarming and human intervention

• Pursuing a Bachelor’s degree or relevant work experience in Computer Science, Mathematics, Electrical Engineering or a related technical discipline.
• Experience developing software in a professional environment (preferably financial services but not required)
• Understanding of Enterprise architecture patterns, Object Oriented & Service Oriented principles, design patterns, and industry best practices
• Foundational knowledge of data structures, algorithms, and designing for performance.
• Competent in one of the following programming languages: Java, C# or Python (preferred) and willingness to learn and adopt new languages as necessary
• Experience in database technology like MSSQL and one of key-value and document databases like MongoDB, Dynamo Db, and Casandra.
• Exposure to containers, microservices, distributed systems architecture, orchestrators and cloud computing.
• Comfortable with core programming concepts and techniques (e.g. concurrency, memory management)
• Enjoys working with algorithms and data structures (e.g. trees, hash maps, queues)
• Data Analytics and Data Science experience will be a plus.
• Good sense of user interaction and usability design to provide an intuitive, seamless end-user experience.
• Excellent communication skills and the ability to work with subject matter experts to extract critical business concepts.
• Ability to work and potentially lead in an Agile methodology environment.