Staff Data Scientist

Ripple Ripple · Fintech · Chicago, IL +1 · Engineering

Staff Data Scientist and Engineer role focused on building and leading a robust, scalable, and resilient data platform for corporate treasury solutions. The role involves technical leadership, collaboration with product teams, system design and architecture, mentoring, and driving agile development methodologies. Requires deep data engineering experience, expertise in ETL, data movement, and various data technologies within a cloud environment. The position also includes on-call responsibilities.

What you'd actually do

  1. Technical Leader Platform Data team to build a robust, scalable and resilient data platform serving all portfolio applications
  2. Collaborate with solution teams, product managers, and deliver robust cloud-based Data platform and solutions
  3. Make decisions on the solution and the design, architecture, and delivery of systems
  4. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community, and evaluating technical design & code
  5. Active coach and mentor to your team and grow them in their skills

Skills

Required

  • Leadership acumen
  • software development lifecycle and engineering excellence processes
  • Agile methodologies
  • project management
  • Deep data engineering experience in complex distributed systems
  • technical acumen
  • Hands-on approach
  • automation with ETL process
  • data movement with data medallion architecture
  • Databricks
  • SQL
  • Python
  • PowerShell
  • C#/.NET
  • SQL Server
  • PostgreSQL
  • Data Lake/Lakehouse
  • Qlik
  • Zoho Analytics
  • Azure PaaS services

Nice to have

  • Izenda
  • SSRS
  • AWS Data Services

What the JD emphasized

  • Technical Leader Platform Data team
  • build a robust, scalable and resilient data platform
  • deliver robust cloud-based Data platform and solutions
  • design, architecture, and delivery of systems
  • mentoring other members of the engineering community
  • evaluating technical design & code
  • coach and mentor to your team
  • drive agile development and analytical methodologies
  • continuously improve the operations, processes, methodologies, technology choices, and practices of the team
  • solution architecture options for design
  • meet quality, operational, and architectural standards
  • YBIYRI model (you-build-it-you-run-it)
  • on-call pager rotation
  • Leadership acumen
  • software development lifecycle and engineering excellence processes
  • Agile methodologies
  • project manage moderately sized projects
  • Deep data engineering experience in complex distributed systems
  • technical acumen
  • Hands-on approach and ready to deep dive into code details
  • automation with ETL process
  • data movement with data medallion architecture
  • Databricks, SQL, Python, PowerShell, C#/.NET, SQL Server, PostgreSQL, Data Lake/Lakehouse, Qlik, Zoho Analytics, Azure PaaS services