Data Platform Architect

  • ELCA
  • Geneva, Geneve, Switzerland
  • 03/08/2019
Full time Data Science Data Analytics Big Data Statistics

Job Description

In this role

  • You will work with business and software engineering teams to build data platforms from the ground up, driven by concrete business use cases
  • You will guide teams on the end-to-end project lifecycle, covering the initial conception, business requirements, software architecture, technical lead, coaching, and flawless delivery
  • You will provide technological and architectural consulting to our clients, create strategic roadmaps and advise on their execution
  • You will support pre-sales on tender responses, proof-of-concept work and the design of modern data platforms, both on premise and in the cloud
  • You will run group-wide thought leadership initiatives to advance our architectural practice and sustain our technical excellence

What we offer

  • A stimulating and professional working environment in a dynamic team with extensive expertise
  • Exciting projects and challenging problems to solve using the latest technologies.
  • Flat organizational hierarchies and cross-functional teamwork
  • Close contact with customers in diverse industries
  • A supportive culture with excellent opportunities for professional and personal development

About your profile

  • 6+ years of experience in designing and implementing large-scale software solutions
  • Hands-on experience in architecting big data systems and analytical pipelines covering data collection, data preparation and storage, data analysis and serving to data scientists or business users
  • Solid knowledge of integration patterns and best practices such as synchronous vs. asynchronous communications, RESTful APIs, messaging, publish-subscribe
  • Deep understanding of distributed systems, real-time vs. (micro-)batch processing and related design principles and patterns
  • Solid knowledge of data-centric patterns, data modelling, query optimization on several storage solutions among SQL databases, document stores, graph databases, time-series databases, data warehouses
  • Experience with one or several distributed streaming / processing platforms such as Kafka, Spark or cloud-based alternatives
  • Strong knowledge of best practices and tooling for CI/CD pipelines, DevOps, automation, agile methods, automated testing, code quality
  • Knowledge of data management best practices; experience with data governance and catalog solutions is a plus
  • Experience in productionizing Machine Learning models is a plus
  • Strong computer science fundamentals such as algorithms and data structures
  • A passion for pragmatic, elegant design
  • Enthusiasm, creativity, flexibility, team spirit, and general awesomeness in software engineering
  • Strong leadership and communication skills
  • Fluent in French and in English. German would be a plus.