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BlackStone eIT
BlackStone eIT
201 – 500 Employees
ConsultingLogisticsMarketing
BlackStone eIT is a global technology and consulting company that develops enterprise solutions focused on digital transformation, intelligent design, and improved customer engagement. Its work spans augmented reality, blockchain, intelligent chatbots, emotion scanning, optical character recognition, robotics, facial and object recognition, and smart analytics. The company also delivers tailored tools such as Arabic natural language processing engines, digital workplaces, facial attendance systems, and scheduling platforms. BlackStone eIT serves organizations across consulting, marketing, and logistics, combining emerging technologies with practical business applications.
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Lead Data Architect (Hybrid, Egypt)

Lead enterprise data architecture, governance, cloud platforms, and migration programs for an Egypt-based organization. Guide data teams and shape scalable solutions across analytics, integration, and AI/ML initiatives.

EGEgyptHybridFull-timeSeniorEnglish RequiredData Engineer
Amazon RedshiftAWSAzureBigQueryCloudERPETLGoogle Cloud PlatformInformaticaKafkaPythonScalaSQLTableau

Description

  • Own the enterprise data architecture strategy, standards, and roadmap in line with business priorities.
  • Create scalable conceptual, logical, and physical models for OLTP, OLAP, data lake, and lakehouse environments.
  • Design data pipelines, ETL/ELT workflows, and integration patterns spanning source systems, warehouses, and downstream applications.
  • Assess and choose appropriate data platforms, tools, and technologies.
  • Establish and apply frameworks for data governance, quality, master data, and metadata management.
  • Lead and develop data architects, engineers, and analysts.
  • Evaluate and approve data architecture designs, models, and technical implementations.
  • Provide technical direction for data security, privacy, access management, and compliance.
  • Promote consistent practices for modeling, naming, version control, and documentation.
  • Work with business, product, and engineering stakeholders to turn requirements into data architecture solutions.
  • Coordinate with BI, analytics, data science, and application teams on reporting, analytics, and AI/ML use cases.
  • Manage data migration, legacy platform retirement, and cloud migration initiatives.
  • Enable integrations with ERP, CRM, and third-party systems.
  • Contribute to architecture review boards and provide technical approval for significant data initiatives.
  • Implement processes for monitoring and resolving data quality issues.
  • Maintain data catalogs, lineage records, and metadata repositories.
  • Ensure architecture meets scalability, performance, security, and cost-efficiency objectives.

Requirements

  • Bring 8–10 years of experience in data architecture, data engineering, or a related field, including 3–5 years in a lead or architect role.
  • Demonstrate hands-on expertise in dimensional, star, snowflake, normalized, and denormalized data modeling.
  • Have deep experience with at least one major cloud data platform, such as AWS Redshift or Glue, Azure Synapse or Data Factory, GCP BigQuery or Dataflow, Snowflake, or Databricks.
  • Use SQL confidently and have experience with ETL/ELT tools such as Informatica, Talend, dbt, or Azure Data Factory.
  • Understand data warehouse, data lake, and/or lakehouse architecture patterns.
  • Know the principles and practices of data governance, master data management, data quality, and metadata management.
  • Have worked with API-based and event-driven integrations, including Kafka, REST, or OIC.
  • Translate business requirements into practical technical architectures while managing stakeholders effectively.
  • Have experience leading and mentoring technical teams.
  • Be familiar with BI and reporting platforms such as Power BI, Tableau, OBIEE, or Looker.
  • Understand data pipeline and feature store requirements for AI and machine learning workloads.
  • Know data security and compliance frameworks including GDPR, HIPAA, and data residency requirements.
  • Relevant certifications in AWS, Azure, or GCP data architecture, Snowflake, Databricks, DAMA, or CDMP are applicable.
  • Bring experience in an industry relevant to the organization, such as finance, healthcare, government, or retail.
  • Program in Python or Scala for data engineering work.
  • Combine strategic judgment, strong technical depth, business understanding, leadership, mentoring, structured problem solving, and clear communication with technical and non-technical stakeholders.

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