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Member of Engineering – Data & Analytics

Jobgether

🇬🇧 English
Go Python Distributed systems Cloud infrastructure Kubernetes Observability systems OLAP databases

Job description

About the role

This position is based in Portugal and focuses on building the foundational data and analytics infrastructure that powers advanced AI research and development. You will design, implement, and operate critical systems that enable experiment tracking, model‑training pipelines, and large‑scale data analysis.

Key responsibilities

  • Design, build, and operate data and analytics platforms supporting AI model development workflows.
  • Own the full lifecycle of experiment data, including modeling, ingestion, retrieval, querying, analysis, and retention.
  • Develop high‑performance, scalable data infrastructure to meet growing reliability and performance demands.
  • Collaborate closely with research teams to translate workflow needs into technical solutions.
  • Build and maintain distributed systems, data pipelines, and analytics platforms.
  • Contribute to greenfield projects while improving and scaling existing systems.
  • Drive technical initiatives by identifying opportunities, defining solutions, and working across teams.
  • Ensure systems are observable, maintainable, and optimized for long‑term growth.

Required profile

  • Proven experience building large‑scale data systems and distributed infrastructure.
  • Strong problem‑solving abilities with a focus on scalable, reliable engineering solutions.
  • Ability to lead complex, ambiguous technical initiatives independently.
  • Experience collaborating with cross‑functional research and engineering teams.

Required skills

  • Programming in Go and/or Python.
  • Design and operation of distributed systems at scale.
  • Knowledge of consistency models, queue/stream processing, and data pipelines.
  • Experience with cloud infrastructure and Kubernetes.
  • Production observability and monitoring systems.
  • Familiarity with OLAP databases, time‑series databases, high‑cardinality datasets, or large‑scale analytics systems.

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Published 1 month ago

Expires 3 weeks from now

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