استخدام Data Engineering Manager

About the Role
 We are looking for an experienced Data Engineering Manager to lead our Data Engineering and Database Administration teams. This role is responsible for defining and executing the organization's data engineering strategy, building and operating a modern enterprise data platform, and enabling data-driven decision-making across the company.
 The ideal candidate is both a strong technical leader and an experienced people manager who can build scalable data architectures, lead engineering teams, ensure operational excellence, and drive modernization initiatives.
 
 Key Responsibilities
Leadership & Team Management
• Lead, mentor, and grow the Data Engineering and DBA teams.
• Recruit, onboard, and develop high-performing engineering talent.
• Define team goals, KPIs , and development plans.
• Promote engineering best practices and a culture of ownership and continuous improvement.
• Plan and prioritize team activities using Agile/Scrum methodologies.
• Collaborate closely with Product, Software Engineering, Infrastructure, BI, and Business stakeholders.
Data Platform & Architecture
• Own the architecture, scalability, and reliability of the enterprise data platform.
• Design and maintain modern Data Warehouses and analytical data platforms.
• Define enterprise data models and architectural standards.
• Design scalable, reusable, and metadata-driven data solutions.
• Drive modernization of legacy data platforms toward modern open-source architectures.
• Establish engineering standards, reusable frameworks, and development guidelines.
Data Engineering
• Design, build, and maintain scalable ETL/ELT pipelines.
• Develop reliable batch and near real-time data processing solutions.
• Build and maintain orchestration workflows using Apache Airflow.
• Ensure data pipelines are fault-tolerant, observable, maintainable, and scalable.
• Improve deployment automation through CI/CD and DataOps practices.
• Standardize engineering processes including testing, deployment, monitoring, and documentation.
Database Administration
Lead the Database Administration (DBA) function responsible for:
• SQL Server administration
• PostgreSQL administration
• MongoDB administration
• Database performance tuning
• Backup and recovery
• High Availability (HA)
• Disaster Recovery (DR)
• Capacity planning
• Database security
• Database lifecycle management
Data Quality & Governance
• Establish enterprise-wide Data Quality standards.
• Implement validation, reconciliation, and monitoring mechanisms.
• Ensure consistency, integrity, and reliability of enterprise data.
• Define metadata, lineage, governance, and documentation standards.
• Monitor data platform SLAs and operational KPIs.
Security & Compliance
• Define and enforce secure data access models.
• Implement role-based access controls and least-privilege principles.
• Collaborate with Security teams to ensure compliance with organizational standards.
• Protect sensitive data through secure engineering practices.
Strategy & Innovation
• Contribute to the organization's data strategy and technology roadmap.
• Evaluate emerging technologies and recommend adoption where appropriate.
• Enable AI-ready data platforms.
• Collaborate with leadership to deliver data-driven business capabilities.
• Drive continuous improvement across the data platform.
Required Technical Skills
Data Platforms
• Enterprise Data Warehouse Architecture
• Data Modeling
• ETL / ELT Design
• Data Pipeline Engineering
• Data Quality
• Data Governance
• DataOps
Databases
• Microsoft SQL Server
• PostgreSQL
• MongoDB or other NoSQL databases
Programming
• Python
• SQL
Data Engineering
• Apache Airflow
• API Integration
• Batch Processing
• Near Real-Time Data Processing
DevOps & Infrastructure
• Git
• CI/CD
• Docker
• Linux
Methodologies
• Agile
• Scrum
Preferred Qualifications
Experience with one or more of the following is considered a strong advantage:
• Kubernetes
• Apache Kafka
• Click House
• ELK Stack
• Prometheus
• Grafana
• dbt
• Apache Spark
• ML-Ops
• AI Engineering
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Large Language Models (LLMs)
• AI-powered Data Platforms
Qualifications
• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 7+ years of experience in Data Engineering.
• 3+ years of experience leading engineering teams.
• Proven experience designing and operating enterprise-scale data platforms.
• Strong analytical, communication, and leadership skills.
• Experience working in Agile/Scrum environments.
Technologies We Use
• Microsoft SQL Server 
• PostgreSQL 
• MongoDB 
• Apache Airflow 
• Python 
• Kubernetes 
• Docker 
• Git Lab 
• CI/CD 
• ELK Stack 
• Prometheus 
• Grafana 
• Power BI 
• SQL Server Analysis Services (SSAS) 
• REST APIs 
• AI & LLM Technologies 

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