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Data Architect
Job summary
A leading data and analytics firm is looking for a Data Architect who can design and lead enterprise data architecture. The role requires strong familiarity with Databricks and Power BI, ensuring reliable data governance and scalable analytics solutions. Responsibilities include owning the data standards, producing clear documentation, and collaborating with various teams to translate business needs into robust data models. Candidates should have a solid coding background, with Python and SQL knowledge. This is a hybrid role based in Riyadh.
Qualifications
- Strong Databricks experience, including Delta Lake and Spark.
- Deep understanding of Power BI's semantic models and security.
- Solid coding background, particularly in Python and SQL.
Responsibilities
- Own end-to-end data architecture, standards, and roadmap.
- Govern curated data using Databricks Unity Catalog.
- Define and maintain Power BI Semantic Models as the single source of truth.
Skills
Education
Tools
Role Brief – Data Architect (Analytics, AI & Platform Governance)
Department: Data & Platform Engineering
Reports to: VP of Data
Location: Hybrid / Riyadh
We are scaling rapidly — expanding products, customers, and acquisitions across global construction markets. Data is now the core connective layer (“Dark Matter”) that must keep pace with this growth.
This role exists to design, and lead enterprise data architecture, ensuring:
- One trusted source of truth for metrics
- Customer-grade embedded analytics at scale
- AI-driven insights built only on governed data
- Fast onboarding of new products, data sources, and acquisitions
Design and operate a best-of-breed, Microsoft-native analytics and AI platform that delivers:
- Reliable ingestion and open lake storage
- Centralized governance and lineage
- A single semantic layer reused across BI, embedded analytics, and AI
- Scalable, secure, multi-tenant customer reporting
- AI summaries, narratives, and future copilots powered by trusted data
The Data Architect Owns And Evolves The Following Architecture
Sources → ADF → ADLS Gen2 (Delta) → Databricks (Silver/Curated, Unity Catalog) → Snowflake / Microsoft Fabric Compute (Power BI) → Power BI Semantic Models → Embedded & Internal Consumption
- Databricks + Unity Catalog as the governance and curation control plane
- AI Powered migration strategies from the current SQL Server Datawarehouse
- Power BI Semantic Models as the single metrics and security layer
- Microsoft Fabric Compute (Power BI context only) for AI summaries, narratives, and LLM-based assistants
- Power BI Embedded for all customer-facing analytics
- Clear separation of customer workloads from internal experimentation
- Own end-to-end data architecture, standards, and roadmap
- Govern curated data using Databricks Unity Catalog (access, lineage, audit)
- Define and maintain Power BI Semantic Models as the single source of truth
- Enable AI-assisted insights, summaries, and story-based reporting
- Architect secure, scalable, multi-tenant embedded analytics
- Partner with product, engineering, and construction ops to translate business needs into durable data models
- Produce clear ERDs, semantic documentation, and platform design artifacts
- Senior-level Data Architect or Analytics Architect
- Strong Databricks experience (Delta Lake, Spark, Unity Catalog)
- Deep understanding of Power BI (semantic models, embedded, security)
- Solid coding background (Python, SQL; Scala a plus)
- Comfortable enabling AI / agentic analytics on governed data
- Experience with high-concurrency customer analytics and multi-tenancy
Experience with construction, industrial IoT, or workforce/safety data domains.
- One trusted semantic model powering all analytics and AI
- Customer dashboards that scale independently and securely
- AI-generated insights embedded directly into executive and customer reports
- Fast, low-friction onboarding of new data sources and acquisitions
- Clear governance, lineage, and documentation adopted across teams
This role defines how we scale with confidence — ensuring data, metrics, and AI remain consistent, explainable, and trusted as the company grows across projects, geographies, and products.
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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.