Data Engineer for Large-Scale Data Products

1 week ago

London, Greater London, United Kingdom Bloomberg Full time
Bloomberg Data Engineer Job Description

We are responsible for delivering data, news, and analytics through innovative technology, quickly and accurately, by combining data and context to paint a complete picture for our clients. Our team collects, analyzes, processes, and publishes the data that forms the backbone of our Bloomberg Terminal.

As a Data Engineer, you will take on the exciting aspects of our data product, from data engineering to business analytics, using various tools. You will develop, scale, and maintain the data pipelines and processes that interact with our structured products and corporate bond databases.

  • Develop, scale, and maintain the data pipelines and processes that interact with our structured products and corporate bond databases.
  • Collaborate with external partners and internal departments on strategic product development and execution.
  • Use statistics and data visualization to generate insights about ongoing operations and projects and communicate the results effectively.
  • Incorporate machine learning and statistics to detect anomalies and drive quality improvement in areas such as accuracy, completeness, consistency, and reliability.
  • Ensure all non-financial risks associated with regulatory data being captured and supervised are minimized, and the appropriate mitigating actions and controls are correctly implemented.
Requirements:
  • 4+ years of Python programming and scripting in a production environment.
  • 4+ years of experience working with databases either SQL or NoSQL.
  • Understanding of Machine Learning, applied statistics, and data analytics.
  • Understanding and experience of large-scale, distributed systems.
  • Strong problem-solving skills, particularly to modify and improve processes and workflows.
  • Excellent written and verbal communication skills to explain technical processes and solutions to business partners and management.

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