Lead Data Architect

BlackStone eIT

. Define and own the enterprise data architecture strategy, standards, and roadmap aligned with business objectives.

Posted 10/7/2026full-timeNasr City • EgyptSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data architecture and engineering, with a strong focus on designing scalable data models, implementing data governance frameworks, and leading technical teams. Proficient in cloud data platforms and ETL/ELT processes, ensuring alignment with business objectives and compliance standards.

Highest-signal resume keywords

Data Architecture StrategyCloud Data Platform ExpertiseETL/ELT Process DesignData Governance FrameworksStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingSQLETL ToolsData WarehousingData LakesAPI IntegrationPythonScalaData Security ComplianceBI Tools

Soft Skills

LeadershipMentoringStrategic ThinkingClear CommunicationStructured Problem Solving

Tools & Technologies

AWS RedshiftAzure SynapseGCP BigQuerySnowflakeDatabricksInformaticaTalendAzure Data FactoryPower BITableau

Certifications & Qualifications

AWS Data ArchitectAzure Data ArchitectGCP Data ArchitectSnowflake CertificationDatabricks CertificationDAMA/CDMP

Industry Keywords

FinanceHealthcareGovernmentRetailData GovernanceMaster Data ManagementData QualityMetadata ManagementGDPRHIPAA

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureBigQueryCloudERPETLGoogle Cloud PlatformInformaticaKafkaPythonScalaSQLTableau

About the role

Key responsibilities & impact

Define and own the enterprise data architecture strategy, standards, and roadmap aligned with business objectives.
Design scalable conceptual, logical, and physical data models across OLTP, OLAP, and data lake/lakehouse environments.
Architect data pipelines, ETL/ELT processes, and integration patterns across source systems, data warehouses, and downstream applications.
Evaluate and select data platforms, tools, and technologies.
Define and enforce data governance, data quality, master data management, and metadata management frameworks.
Lead and mentor data architects, data engineers, and/or analysts.
Review and approve data architecture designs, data models, and technical solutions.
Set technical direction on data security, privacy, access control, and compliance.
Drive best practices in data modeling, naming conventions, version control, and documentation.
Partner with business stakeholders, product owners, and engineering teams to translate requirements into data architecture solutions.
Collaborate with BI/Analytics, Data Science, and application teams for reporting, analytics, and AI/ML use cases.
Oversee data migration, legacy system decommissioning, and cloud migration projects.
Support integrations across ERP, CRM, and third-party applications.
Participate in architecture review boards and provide technical sign-off on major data initiatives.
Establish data quality monitoring and remediation processes.
Define and maintain data catalogs, data lineage, and metadata repositories.
Ensure architecture supports scalability, performance, security, and cost optimization.

Requirements

What you’ll need

8-10 years of experience in data architecture, data engineering, or related roles, with at least 3-5 years in a lead/architect capacity.
Strong hands-on experience designing data models (dimensional modeling, star/snowflake schemas, normalized/denormalized models).
Deep expertise in at least one major cloud data platform (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow, Snowflake, Databricks).
Strong SQL skills and experience with ETL/ELT tools (Informatica, Talend, dbt, Azure Data Factory, etc.).
Experience with data warehousing, data lakes, and/or lakehouse architectures.
Solid understanding of data governance, MDM, data quality, and metadata management principles.
Experience with API-based and event-driven integration (Kafka, REST, OIC, etc.).
Strong stakeholder management and ability to translate business needs into technical architecture.
Experience leading and mentoring technical teams.
Experience with BI/reporting tools (Power BI, Tableau, OBIEE, Looker).
Familiarity with AI/ML data pipeline requirements and feature stores.
Experience with data security/compliance frameworks (GDPR, HIPAA, data residency).
Relevant certifications (AWS/Azure/GCP Data Architect, Snowflake, Databricks, DAMA/CDMP).
Experience in a specific industry vertical relevant to the hiring organization (Finance, Healthcare, Government, Retail).
Programming experience in Python or Scala for data engineering tasks.
Strategic thinking, strong technical depth combined with business acumen, leadership and mentoring ability, structured problem solving, clear communication with both technical and non technical stakeholders.