BlackStone eIT

System integrator delivering AI-enabled digital transformation

Data Architect Lead

Data ManagementConfirmed live in the last 24 hours

Full-timeAmman, JordanNo salary listedIn-person

About the Job

Requirements

8–10 years of experience in data architecture, data engineering, or related roles, including at least 3–5 years in a lead or architect capacity.
Strong hands-on experience designing conceptual, logical, and physical data models, including dimensional modeling, star and snowflake schemas, and normalized or denormalized models.
Deep expertise in at least one major cloud data platform: AWS Redshift or Glue, Azure Synapse or Data Factory, GCP BigQuery or Dataflow, Snowflake, or Databricks.
Strong SQL skills and experience with ETL/ELT tools such as Informatica, Talend, dbt, or Azure Data Factory.
Experience with data warehousing, data lakes, or lakehouse architectures.
Understanding of data governance, master data management, data quality, and metadata management principles.
Experience with API-based and event-driven integration, including Kafka, REST, or OIC.
Experience translating business needs into technical architecture and managing stakeholder relationships.
Experience leading and mentoring technical teams.

Responsibilities

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

Desired Qualifications

Experience with business intelligence and reporting tools such as Power BI, Tableau, OBIEE, or Looker.
Familiarity with AI/ML data pipeline requirements and feature stores.
Experience with data security and compliance frameworks such as GDPR, HIPAA, or data residency requirements.
Relevant AWS, Azure, or GCP Data Architect, Snowflake, Databricks, DAMA, or CDMP certifications.
Experience in an industry vertical relevant to the hiring organization, such as finance, healthcare, government, or retail.
Programming experience in Python or Scala for data engineering tasks.

Data Architect Lead

BlackStone eIT · Amman, Jordan · Full-time · Posted 2026-10-06

Workplace: on_site

Department: Technical Team

Description

Role Purpose

Own the end-to-end data architecture strategy for the organization, leading the design of scalable,

secure, and high-performing data platforms. Act as the technical authority on data modeling,

integration, governance, and infrastructure, while leading a team of data architects/engineers and

guiding cross-functional stakeholders on data-driven initiatives.

Key Responsibilities

Architecture & Strategy

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

• Design scalable data models (conceptual, logical, physical) 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 appropriate data platforms, tools, and technologies (cloud data warehouses, lakehouses, streaming platforms).

• Define and enforce data governance, data quality, master data management (MDM), and metadata management frameworks.

Technical Leadership

• Lead and mentor a team of data architects, data engineers and/or analysts.

• Review and approve data architecture designs, data models, and technical solutions proposed by the team.

• Set technical direction on data security, privacy, access control, and compliance (e.g. GDPR, data residency requirements).

• Drive adoption of best practices in data modeling, naming conventions, version control, and documentation.

Delivery & Collaboration

• Partner with business stakeholders, product owners, and engineering teams to translate business requirements into data architecture solutions.

• Collaborate with BI/Analytics, Data Science, and application teams to ensure data is structured for reporting, analytics and AI/ML use cases.

• Oversee data migration strategies, including legacy system decommissioning and cloud migration projects.

• Support integration projects, ensuring consistent and reliable data flow across systems (ERP, CRM, third-party applications).

• Participate in architecture review boards and provide technical sign-off on major data initiatives.

Governance & Quality

• Establish data quality standards, monitoring, and remediation processes.

• Define and maintain data catalogs, data lineage, and metadata repositories.

• Ensure architecture decisions support scalability, performance, security, and cost optimization.

Requirements

Requirements

• 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. Desirable

• 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.

Key Competencies

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.

Apply

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About the Company

BlackStone eIT

System integrator delivering AI-enabled digital transformation

Blackstone eIT is a system integrator and independent software vendor that helps organizations modernize through customized technology solutions across strategy, development, and managed services. It combines consulting, custom software, IT governance, workflow automation, and UI/UX design with hosted data storage, network, and security to support the full digital transformation lifecycle. It emphasizes long-term partnerships and uses intelligent technologies such as AI, machine learning, computer vision, big data analytics, blockchain, and IoT, including Agentic AI and Generative AI across its offerings and proprietary products like a Business Excellence Suite, Learning Management System, e-invoicing platform, Carbon Management Platform, and archiving system. Its goal is to help clients become digital-first, data-informed, and AI-enabled, with the aim of reducing costs and improving operational efficiency across finance, education, government, and manufacturing.

Company size: 201-500
Company stage: Not listed
Total funding: Not listed
Headquarters: Seattle, WA
Founded: 2014

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