обновлено 5 дней назад
Director, Data Engineering (Google Cloud Platform)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Director, Data Engineering (Google Cloud Platform) (GCP, Generative AI): Leading the GCP data engineering function and delivering enterprise data platforms for advanced analytics, AI/ML, and digital transformation with an accent on modern data architecture, real-time analytics, GenAI infrastructure, and governance. Focus on designing scalable BigQuery and Dataflow pipelines, vector search and RAG infrastructure, Terraform-based delivery, and mentoring agile engineering teams.
Location: Remote, Austin, TX, United States
Company
delivers employee-first customer experience solutions and enterprise digital transformations.
What you will do
- Define the technical vision and standards for the GCP Data Engineering practice, including data modeling, ingestion pipelines, lakehouse architecture, and cloud cost optimization.
- Oversee the design and deployment of enterprise data platforms using BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex, and Cloud Storage.
- Build production-grade data pipelines, vector search infrastructure, and retrieval-augmented generation frameworks for Generative AI and ML use cases.
- Lead GCP-native data governance, security, compliance, lineage, access controls, and metadata management.
- Support pre-sales, client workshops, and enterprise delivery engagements as a GCP Data subject matter expert.
- Manage, mentor, and scale an agile team while driving hiring, skills development, certifications, and performance management.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 10+ years of experience in data engineering and enterprise architecture, including 5+ years managing engineering teams.
- 4+ years of hands-on experience designing production data solutions on Google Cloud, including BigQuery, Dataflow, Pub/Sub, Cloud Composer or Airflow, Dataproc, and Cloud Storage.
- Advanced SQL and Python skills, with experience in LLM data pipelines, vector search indexing, GenAI workflows, Apache Beam, PySpark, and NoSQL databases.
- Experience with modern data modeling, ELT/ETL architecture, real-time streaming, and Medallion or Lakehouse architectures.
- Strong knowledge of Terraform, CI/CD, IAM, KMS, Knowledge Catalog governance, data security, stakeholder management, and consultative delivery.
Nice to have
- Google Cloud Professional Data Engineer certification.
Culture & Benefits
- Remote workplace.
- Leadership role within the Data and Analytics team.
- Focus on mentoring high-performing engineering teams and supporting Google Cloud certification pathways.
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