Senior Manager, Data Engineering & Platform

San Francisco, CA, United States

Applications have closed

Ripple

Ripple is the leading provider of crypto solutions for businesses. Learn how we’re helping organizations of all sizes drive impact with the power of crypto.

View company page

Ripple’s mission is to enable payments every way, everywhere for everyone. We believe connecting traditional financial entities like banks, payment providers and corporations with emerging blockchain technologies and users is the path to an open, decentralized, and more inclusive financial future. This Internet of Value gives any internet-enabled person, application or device access to financial services that are transparent, fast, reliable, and cheap. Delivering this vision is a challenge of massive scale spanning $155 trillion in annual cross border fiat payments and the $1.5 trillion market of digital assets that has grown 10X in the last year. 

Data is the foundation of Ripple’s business, powering both strategic product decisions and products themselves.  The Data Engineering team is responsible for providing data platforming and infrastructure solutions to scale the use of data company-wide. Ripple is looking for an experienced Manager of Data Engineering to spearhead our Data Engineering efforts within the broader Data team. You will mentor, lead and grow a team of talented Data Engineers, and provide visionary thought leadership around how data platforming and tooling can drive the business forward.

 

WHAT YOU’LL DO:

  • Manage and mentor a team of engineers responsible for designing, building and operating our growing data platform.
  • Support our Data Science, Analytics and Machine Learning teams as well as externally-facing product applications.
  • Mentor Data Engineers to improve and maintain data platforms, pipelines and tools to keep pace with the growth of our data and its consumers. This includes internal (employees) external (customer) stakeholders.
  • Identify and analyze requirements and use cases from multiple internal teams (including Finance, Compliance, Data Science, Product, and Engineering) and work with other technical leads and product managers to design solutions for the requirements
  • Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals
  • Instill a spirit of continuous improvement in the team’s code, architecture, and processes

 

WHAT WE’RE LOOKING FOR:

  • 10+ years of data platform and engineering experience
  • 3+ years building and mentoring high-powered data engineering teams
  • 5+ years working in Java and Python
  • Exceptional communication skills, demonstrated through experience working with technical and non-technical teams
  • Deep experience with distributed systems, distributed data stores, data pipelines and other tools in cloud services environments (e.g AWS, GCP)
  • Extensive experience partnering with Data Analytics, Data Science and/or Machine Learning Teams to build data solutions for internal stakeholders
  • Deep experience with Google Cloud Platform (GCP), and/or AWS data ecosystems  
  • Hands on experience with Kubeflow/MLFlow or other ML lifecycle management tools preferred
  • Demonstrated success building scalable self-service data platforms
  • Demonstrated success in building a platform for moving, storing and making data available for internal+external producers+consumers.
  • Experience with real-time stream processing frameworks such as Apache Beam and Spark

 

WHAT WE OFFER:

  • The chance to work in a fast-paced start-up environment with experienced industry leaders
  • A learning environment where you can dive deep into the latest technologies and make an impact
  • Competitive salary and equity
  • 100% paid medical and dental and 95% paid vision insurance for employees starting on your first day
  • 401k (with match), commuter benefits
  • Industry-leading parental leave policies
  • Generous wellness reimbursement and weekly onsite programs
  • Flexible vacation policy - work with your manager to take time off when you need it
  • Employee giving match
  • Modern office in San Francisco’s Financial District
  • Fully-stocked kitchen with organic snacks, beverages, and coffee drinks
  • Weekly company meeting - ask me anything style discussion with our Leadership Team
  • Team outings to sports games, happy hours, game nights and more!

WHO WE ARE:

Ripple enables payments everywhere, every way, for everyone using the power of blockchain. By joining Ripple’s growing, global network (RippleNet), financial institutions can process their customers’ payments anywhere in the world instantly, reliably and cost-effectively. Banks and payment providers can use the digital asset XRP to further reduce their costs and access new markets.

  Ripple is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.   Please find our UK/EU applicant privacy notice here.

Tags: AWS Blockchain Data Analytics Data pipelines Distributed Systems Engineering Finance GCP Google Cloud Machine Learning MLFlow Pipelines Python Spark

Perks/benefits: 401(k) matching Career development Competitive pay Equity Flex hours Flex vacation Health care Insurance Medical leave Parental leave Snacks / Drinks Startup environment Team events Wellness

Region: North America
Country: United States
Job stats:  6  1  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.