Data Pipeline Architect

2 months ago

London, Greater London, United Kingdom Tether Operations Limited Full time
About Tether Operations Limited

Tether Operations Limited is a pioneering company in the field of artificial intelligence, committed to making advanced AI technologies more accessible. Our investment in AI infrastructure has positioned us for tackling ambitious AI projects, and our goal is to build the next generation of AI models, leading innovation in AI through an accessible, transparent, and privacy-preserving approach.

Job Summary

We are seeking a highly skilled Data Pipeline Engineer to join our dynamic team, which operates entirely remotely, uniting talent from every corner of the globe. As a Data Pipeline Engineer, you will play a crucial role in building AI solutions across the spectrum, from large-scale models designed for advanced applications to smaller, highly performant models tailored for efficiency on edge devices such as mobile phones and laptops.

Key Responsibilities
  • Design and Development: Design, build, and maintain efficient, reusable, and reliable Python code to construct data pipelines, ensuring high performance, quality, and responsiveness.
  • Collaboration and Communication: Work closely with data scientists and analysts to understand and fulfill their data requirements, ensuring seamless integration and effective communication.
  • Problem-Solving and Optimization: Identify bottlenecks and bugs, and devise solutions to these problems, maintaining code quality, organization, and automatization.
  • Data Collection and Integration: Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality, collaborating with teams to integrate systems.
Requirements
  • 4+ years of experience in a Data Pipeline Engineer role.
  • Strong programming skills in Python.
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases.
  • Strong analytic skills related to working with unstructured datasets.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
Preferred Qualifications
  • Degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
  • Experience with machine learning algorithms and libraries.
  • Familiarity with data visualization tools.

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