BlackStone eIT
BlackStone eIT
BlackStone eIT — цифрлық трансформацияға, интеллектуалды дизайнға және клиенттермен өзара әрекеттесуді жақсартуға бағытталған корпоративтік шешімдер әзірлейтін жаһандық технологиялық және консалтингтік компания. Компанияның қызметі толықтырылған шындық, блокчейн, интеллектуалды чат-боттар, эмоцияларды сканерлеу, оптикалық таңбаларды тану, робототехника, бет пен нысандарды тану және ақылды аналитика салаларын қамтиды. Сонымен қатар BlackStone eIT араб тілін табиғи өңдеуге арналған қозғалтқыштар, цифрлық жұмыс орындары, бетті тану арқылы қатысуды тіркеу жүйелері және жоспарлау платформалары сияқты арнайы құралдарды ұсынады. Компания консалтинг, маркетинг және логистика салаларындағы ұйымдарға қызмет көрсетіп, озық технологияларды практикалық бизнес шешімдерімен ұштастырады.

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.

Сипаттама

  • 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.

Талаптар

  • 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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