Resumo da vaga

Data Engineer

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

The Data Engineer Role.

  • Design, build, and operate large-scale data processing pipelines handling multi-terabyte and streaming datasets, including audio/video transcoding, feature extraction, and preprocessing workflows.
  • Deploy, scale, and troubleshoot containerized workloads on Kubernetes and AWS in production environments.
  • Build and maintain distributed data processing jobs using frameworks such as Spark and Ray.
  • Design and operate workflow orchestration systems (e.g., Airflow) with dependency management, retries, monitoring, and alerting for production pipelines.
  • Administer and tune enterprise databases, including performance tuning, backup/recovery, access control, and scaling strategies.
  • Partner with ML engineers and researchers to support training pipelines, model retraining triggers, feature stores, and other MLOps workflows.

Who you are.

  • Hands-on experience with Kubernetes and AWS, including deploying, scaling, and troubleshooting containerized workloads in production environments.
  • Proficiency with high-performance/distributed computing frameworks such as Spark and Ray for processing large-scale datasets.
  • Experience with workflow orchestration tools such as Airflow (or comparable systems like Dagster, Prefect, or Luigi) to schedule and manage complex data pipelines.
  • Strong programming skills in Python and SQL; experience with Golang is a plus.
  • Demonstrated track record building and operating large-scale data processing pipelines, ideally handling multi-terabyte or streaming datasets.
  • Experience working with audio or video data at scale is a strong plus (e.g., transcoding, feature extraction, or preprocessing pipelines).
  • Familiarity with common data transformation patterns applied to large datasets (ETL/ELT, batch and stream processing, data validation and quality checks).
  • Experience designing and maintaining job orchestration systems, including dependency management, retries, monitoring, and alerting for production pipelines.
  • Bonus: experience orchestrating machine learning workflows (training pipelines, model retraining triggers, feature stores, or MLOps tooling).

What we offer.

  • Healthcare plans with 100% premium coverage for employees and partial coverage available for dependents
  • Dental and Vision plans with 100% premium coverage for employees and their dependents
  • Short/Long-term disability and life insurance plans with 100% premium coverage for employees
  • FSA/HSA and 401k programs
  • Equity compensation
  • 20 days of PTO per year
  • 12 weeks of Parental Leave
  • Learning and Development budget
  • Monthly wellness benefits
  • Annual company-sponsored offsite

What we offer.

  • Daily in-office lunch through UberEats
  • Commuter benefits
  • Remote Fridays
  • Happy Hours and other local events
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FocoData EngineerÁrea da vaga
Sinal de senioridadeMiddleNível do candidato
StackAWS, Golang, KubernetesSkills principais
Localização1 país aceitoElegibilidade

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