Senior Specialist, Data Base & Data Mart

Maaden Saudi Arabian Mining Company

Saudi Arabia

On-site

SAR 180,000 - 300,000

Full time

2 days ago

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Job summary

Maaden Saudi Arabian Mining Company seeks a Senior Specialist, Data Base & Data Mart to design scalable enterprise data foundations supporting analytics, reporting, and AI initiatives. You will lead data architecture, modeling, and governance to ensure secure, reliable insights across the organization.

Responsibilities include delivering scalable DB/data mart solutions, ETL/ELT development, performance optimization, and cross-functional collaboration with engineering and governance teams.

Qualifications

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related discipline.
Master's degree in Data Engineering, Data Architecture, Analytics, or a related field is advantageous.

Responsibilities

Deliver scalable database and data mart solutions that support analytics and AI initiatives.
Translate requirements into logical and physical data models aligned with enterprise standards.
Establish reusable design patterns for long-term scalability and maintainability.
Develop robust ETL/ELT processes and data integration practices.
Ensure production deployment, testing, and transition to production are effective.
Optimize performance through tuning, indexing, and capacity management.
Embed data governance, security, and quality controls across solutions.
Collaborate with engineering, governance, analytics, and business teams.

Skills

Database Architecture

Dimensional Data Modeling

Data Mart & Data Warehouse Design

ETL/ELT Development

SQL Performance Optimization

Data Quality & Governance

Cloud Data Platforms

Data Integration & Orchestration

Security, Privacy & Audit Controls

Release & Environment Management

Technical Leadership

Stakeholder Management

Cross-Functional Collaboration

Problem Solving & Root Cause Analysis

Communication & Knowledge Sharing

Mentoring & Coaching

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related

Master's degree in Data Engineering, Data Architecture, Analytics, or related (advantageous)

Job description

1. Why This Role Matters

The Senior Specialist, Data Base & Data Mart enables trusted, scalable, and high-performance data foundations that support analytics, reporting, AI, and business decision-making across Maaden. The role ensures enterprise data assets are structured, governed, and optimized to deliver reliable insights that improve operational and strategic outcomes.

The role strengthens Maaden's Data & AI ecosystem by translating complex business and analytical requirements into robust database and data mart solutions. Through technical leadership and engineering excellence, it improves data accessibility, quality, performance, and governance while ensuring enterprise standards are consistently applied.

By providing expertise in data architecture, database optimization, and lifecycle management, the role enables data-driven transformation initiatives and ensures that enterprise data platforms remain secure, resilient, and aligned with long-term business objectives.

2. What You Will Deliver

Database & Data Mart Architecture

Deliver scalable and high-performing database and data mart solutions that support enterprise analytics, reporting, and AI initiatives.
Translate business and analytical requirements into logical and physical data models aligned with enterprise architecture standards.
Establish reusable design patterns that improve consistency, maintainability, and long-term scalability.

Data Integration & Solution Delivery

Enable reliable delivery of enterprise data through robust ETL/ELT processes, transformation logic, and data integration practices.
Ensure solutions are deployed, tested, and transitioned into production effectively and sustainably.
Improve delivery quality through technical reviews, architecture compliance, and engineering best practices.

Performance & Operational Reliability

Optimize database and data mart performance through tuning, workload analysis, indexing, and capacity management.
Strengthen operational resilience through effective monitoring, issue resolution, recovery planning, and preventive improvements.
Improve platform availability and reliability while supporting growth in business and analytical demand.

Data Governance & Security

Embed data quality, lineage, metadata, ownership, retention, and governance requirements within enterprise data solutions.
Ensure data assets remain secure, auditable, and compliant with corporate policies and regulatory requirements.
Reduce data risk through proactive assessment and remediation of control gaps and quality issues.

Stakeholder Engagement & Delivery Excellence

Partner with engineering, analytics, governance, architecture, cybersecurity, and business teams to deliver prioritized data capabilities.
Provide technical guidance that improves delivery decisions, solution quality, and stakeholder confidence.
Communicate technical recommendations, trade-offs, and constraints in a clear and business-focused manner.

Continuous Improvement & Capability Building

Drive adoption of modern database, cloud, automation, and observability practices that enhance value and efficiency.
Strengthen engineering capability through standards, reusable assets, mentoring, and knowledge sharing.
Improve delivery consistency and operational maturity through continuous enhancement initiatives.

3. What Success Looks Like

Enterprise databases and data marts consistently deliver reliable, accurate, and timely data for analytics and business reporting.
Data performance, availability, and scalability improve through proactive optimization and engineering best practices.
Data governance requirements including lineage, metadata, ownership, and quality controls are embedded across solutions.
Production incidents and performance issues are resolved effectively with reduced recurrence.
Stakeholders have confidence in the quality, accessibility, and reliability of enterprise data assets.
Modern data engineering practices improve delivery efficiency, maintainability, and long-term platform sustainability.

4. Minimum Qualifications

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related discipline.
Master's degree in Data Engineering, Data Architecture, Analytics, or a related field is advantageous.

5. Experience

7-10 years of progressive experience in database development, data engineering, data warehousing, business intelligence, or related disciplines.
Experience designing enterprise-scale data marts, dimensional models, and database solutions.
Experience optimizing high-volume databases and resolving complex production and performance issues.
Experience leading technical delivery across cross-functional stakeholders and technology teams.

6. Skills That Matter

Functional Expertise