Remote Lead, Big Data Platform & Pipelines

Turtle Trax S.A.

United States

Remote

USD 150.000 - 210.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Turtle Trax S.A. is seeking a Big Data Engineering Lead to provide technical leadership for the Data Foundation platform.

You will steer the design and delivery of scalable data pipelines, data products, canonical models, and data services that empower analytics, AI, integration, and operational reporting. The ideal candidate is a hands-on leader with deep expertise in modern data architectures, distributed processing, and engineering excellence.

Qualifikationen

  • 8+ years in data engineering or enterprise data platforms.
  • 3+ years in technical leadership of engineering teams or large data initiatives.
  • Experience designing and delivering enterprise data platforms, pipelines, and data products.
  • Experience in agile software development environments.

Aufgaben

  • Lead the Data Foundation platform's engineering delivery and quality.
  • Oversee building and maintaining enterprise data pipelines, data products, and canonical models.
  • Partner with Service Owner, Architecture, and Platform Engineering to deliver scalable data solutions.
  • Mentor a high-performing data engineering team and drive engineering excellence.

Kenntnisse

Advanced SQL and data modeling
Python and PySpark
ETL/ELT architectures
Master Data Management
RESTful APIs and data services
GraphQL and modern integration
Microservices architectures
Event-driven and real-time processing
Data quality, metadata, lineage

Jobbeschreibung

Turtle Trax S.A. is seeking a Big Data Engineering Lead to provide technical leadership for the Data Foundation platform.

You will steer the design and delivery of scalable data pipelines, data products, canonical models, and data services that empower analytics, AI, integration, and operational reporting. The ideal candidate is a hands-on leader with deep expertise in modern data architectures, distributed processing, and engineering excellence.

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