Steps Ahead

JOIN A TEAM TRANSFORMING THE WAY MARKETS USE DATA

MOSAIC

______________________

THE NEW STANDARD IN

FICC DATA ANALYTICS

Careers

Core Engineer

  • Own features from design to deployment
  • Work with technology and data science teams to understand application requirements
  • Write tests, API and deployment documentation

Required

  • 3 + years hands on development experience
  • Java, SQL, Data Structures and Algorithms
  • Experience with Kafka and other distributed systems is a PLUS

Desirable

  • Big Data Sets and real-time analytics software
  • Python, Bash Scripting, Apache Spark, Scala
  • DevOps and cloud-based infrastructures

The successful candidate will join a small team of highly skilled engineers and data scientists working on a highly innovative FinTech product. The successful candidate will:

  • Contribute to a real-time analytics platform that is highly scalable and extensible for a variety of problems at the intersection of Big Data Analytics, Finance and AI.
  • Work in an engineering team that thrives on deep technical problem solving in a highly collaborate setting.
  • Expand technical skillset and experience (see list of technologies used above)
  • Get exposure to complete software development lifecycle using an agile delivery model.
  • Gain an understanding of what’s required to build and scale a successful start-up.
  • Build tools for use by the world’s largest investment banks.
  • Build knowledge of financial products and complex financial analytics.
  • Work with the data science team to create machine learning pipelines that mine massive datasets
  • Gain an understanding of machine learning and AI algorithms.

Data Platform Implementation Engineer

  • Deploy Mosaic software to clients and integrate it with clients’ systems. This will include configuring existing adapters and developing new ones
  • Provide tooling and automation to aid the implementation process and on-going support. This will include configuration management, systems monitoring and user monitoring. The solutions can be developed in-house or provided by a 3rd party
  • Automation of the process for software build and deployment
  • Work with technology and data science teams to understand application requirements
  • Write tests, API, deployment and production support documentation
  • Prioritize, investigate, track and resolve issues assigned to engineering
  • Respect customers’ cultures and norms, whilst maintaining Mosaic’s standards and acting as an ambassador for Mosaic.

Required

  • 5+ years commercial technical experience to include at 2+ years hands-on Java development experience and 2+ years in customer facing roles
  • Hands on experience in automating software processes using both custom written scripts and tools and commercially available solutions
  • Experience with configuration, deployment and distribution tools (examples – Ansible, Chef, Puppet,Salt, Kubernetes, Terraform)
  • Experience with support and monitoring tools (examples – Nagios, ITRS, Splunk, Graphana, Elastic Search)
  • Hands on experience with Jenkins, Docker

Desirable

  • Experience deploying and managing Apache Kafka, Apache, HDFS clusters
  • Experience working with big data sets (preferably financial data)
  • Experience deploying, managing and supporting complex, mission-critical platforms into large organisations (preferably financial services)
  • Experience deploying software to customers as part of a professional services function

The successful candidate will join a small team of highly skilled engineers and data scientists working on a highly innovative FinTech product. The successful candidate will:

  • Expand technical skillset and experience (see list of technologies used above)
  • Get exposure to complete software development lifecycle using an agile delivery model.
  • Gain an understanding of what’s required to build and scale a successful start-up.
  • Build tools for use by the world’s largest investment banks.
  • Build knowledge of financial products and complex financial analytics.
  • Work with the data science team to create machine learning pipelines that mine massive datasets
  • Gain an understanding of machine learning and AI algorithms.
  • Learn how to manage customer relationships.

Python Engineer

  • Work as part of cross-disciplinary teams, driving both the solution and implementation to complex application requirements from conceptualisation to production.
  • Write tests, API, deployment and production support documentation
  • Assist in the mentoring of junior engineers

Required

  • Strong Computer Science fundamentals
  • Professional Python development experience
  • Experience delivering high-quality production Python code
  • Experience working efficiently in large codebases with legacy components
  • Track record of contributions to solution specification and design documentation
  • Experience supporting production systems
  • Working knowledge of Bash, SQL
  • Worked with relational DBs from Python and a passion for TDD
  • Active team member willing to help and mentor colleagues across disciplines
  • Strong advocate for engineering best practices: unit and integration testing, code review, documentation

Desirable

  • Experience working with Celery, Kafka and other distributed systems
  • Experience working with big data sets and real-time analytics software
  • Experience handling time-series data
  • Deployment and management of Machine Learning models in production
  • Have worked in languages outside of Python, in particular Java
  • Conversant in the web stack: JavaScript, HTML, CSS, React
  • Familiarity with tools such as Ansible, Docker, Jenkins, ELK Stack
  • Experience with cloud-based infrastructures, preferably with AWS
  • Domain knowledge in finance and investment banking a plus

The successful candidate will join a small team of highly skilled engineers and data scientists working on a highly innovative FinTech product. The successful candidate will:

  • Expand technical skillset and experience (see list of technologies used above)
  • Get exposure to complete software development lifecycle using an agile delivery model.
  • Gain an understanding of what’s required to build and scale a successful start-up.
  • Build tools for use by the world’s largest investment banks.
  • Build knowledge of financial products and complex financial analytics.
  • Work with the data science team to create machine learning pipelines that mine massive datasets
  • Gain an understanding of machine learning and AI algorithms.
  • Learn how to manage customer relationships.