Rackspace Technology
Rackspace Technology
Rackspace Technology — кәсіпорындарға көпбұлтты, гибридті және жекеменшік бұлтты орталарды жобалауға, құруға, көшіруге және басқаруға көмектесетін жаһандық басқарылатын бұлттық қызметтер провайдері. Компанияның қызметі бұлттық инфрақұрылымды, қолданбаларды жаңғыртуды, деректер платформаларын, жасанды интеллект пен машиналық оқытуды, киберқауіпсіздікті, басқарылатын хостингті, колокацияны және жетекші гиперскейлерлермен интеграцияны қамтиды. Rackspace реттелетін және қызметі аса маңызды ұйымдарға консалтинг, кәсіби және басқарылатын қызметтерді ұсына отырып, қауіпсіздікке, талаптарға сәйкестікке, шығындарды оңтайландыруға және сенімді операцияларға басымдық береді. Компания командалары консалтинг, логистика және жасанды интеллектке қатысты салаларда жұмыс істеп, күрделі корпоративтік бұлттық бағдарламалармен байланысты түрлі технологиялық рөлдерді ұсынады.

Data Engineer V (Hybrid, United States)

Lead data engineering strategy for enterprise data warehouse pipelines and AI/RAG infrastructure at Rackspace Technology. Guide engineers, delivery standards, stakeholder roadmaps, operational metrics, and pipeline reliability.

Сипаттама

  • Set technical direction, delivery standards, and daily execution for a data engineering pod
  • Manage the roadmap for core enterprise data warehouse pipelines and AI/RAG data infrastructure
  • Convert stakeholder priorities into actionable technical plans
  • Lead, mentor, and prioritize work across an engineering team
  • Coordinate Agile delivery and cross-functional handoffs with data science, security, and compliance teams
  • Establish standards for source management, version control, quality assurance, testing, and AI-assisted coding
  • Define the team metrics strategy, including SLA and SLO monitoring
  • Report pipeline uptime, MTTR, and data-quality KPIs to leadership after analyzing performance trends
  • Develop recovery plans to restore target performance when KPIs fall short
  • Direct root-cause analysis and remediation for complex pipeline and data-quality problems
  • Act as the primary technical contact for business and clinical stakeholders
  • Provide cost and budget input for cloud services and AI or vector-database usage
  • Maintain documentation, standard operating procedures, and escalation processes
  • Help manage the on-call rotation and lead escalations during incidents
  • Apply security and privacy requirements across the team's work

Талаптар

  • Bachelor's degree in computer science, a related technical discipline, or equivalent practical experience
  • 8–12 years in technology roles, including substantial data-focused leadership
  • 6–8 years designing and implementing cloud-based data architectures
  • At least 2 years of formal experience leading engineers or technical workstreams
  • Expertise in SQL, data modeling, and semantic-layer architecture
  • Experience building batch and streaming systems with Spark, Airflow, Databricks, or Snowflake
  • Practical experience with CI/CD methodologies
  • Experience designing AI/RAG data pipelines, including embeddings, vector-store selection, and corpus curation
  • Experience using AI-assisted software development practices
  • Ability to mentor engineers, prioritize team workloads, and deliver Agile work on schedule
  • Ability to turn ambiguous business needs into clear technical plans and present to stakeholders and groups of 10 or more
  • Working knowledge of security and privacy requirements, including risks specific to AI
  • Cloud Professional Data Engineer or ML Engineer certification preferred
  • Healthcare compliance experience with frameworks such as HIPAA, HL7, or FHIR preferred
  • Experience establishing scalable LLM/RAG data architecture standards preferred

Артықшылықтар

  • Annual bonus or incentive compensation
  • Equity awards
  • Employee Stock Purchase Plan (ESPP)
  • Employee benefits, with details provided through Rackspace benefits information
  • Equal employment opportunity
  • Disability or special-needs accommodation

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