AI-Powered Data Architect for Transformative AI Pipelines

Searce Inc

Riyadh

On-site

SAR 300,000 - 600,000

Full time

3 days ago
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Job summary

Searce Inc in Riyadh is seeking a mid-senior Solutions Architect for data engineering. You will drive AI-powered transformations by designing and delivering cloud-native data architectures and scalable data products.

You will engage with clients as the primary technical voice, translating business challenges into actionable data solutions. You will collaborate across engineering, data science, and delivery teams to ensure production-grade data pipelines and governance, enabling fast, reliable

Qualifications

  • Architectural pedigree: 8+ years of AI-driven, cloud-native data transformations.
  • Client-facing technical authority with DRI responsibilities.
  • Cloud and AI-native fluency across major cloud platforms.
  • Experience with Lakehouse, Real-time Streaming, and Platform Migrations.
  • Production-grade automation and DataOps awareness.

Responsibilities

  • Own the technical data solution delivery that fuels client revenue and success.
  • Architect and deliver data products that build client trust and data-driven decision making.
  • Collaborate with hyperscalers, modern data stack ISVs, and AI platforms to enable pipelines and storage capabilities.
  • Lead discovery workshops and translate business problems into elegant data architectures.
  • Architect scalable data products from ingestion to production, ensuring high quality outcomes.

Skills

Data architecture
Cloud platforms
AI/GenAI
Data modeling
Stakeholder communication

Tools

Snowflake
Databricks
Python
SQL
GCP/AWS/Azure

Job description

Searce Inc in Riyadh is seeking a mid-senior Solutions Architect for data engineering. You will drive AI-powered transformations by designing and delivering cloud-native data architectures and scalable data products.

You will engage with clients as the primary technical voice, translating business challenges into actionable data solutions. You will collaborate across engineering, data science, and delivery teams to ensure production-grade data pipelines and governance, enabling fast, reliable

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