Senior Specialist Data Base & Data Mart

About the Role

Key Responsibilities

• 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 to improve consistency, maintainability, and long-term scalability.
• 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.
• 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.
• 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.
• 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.
• Drive adoption of modern database, cloud, automation, and observability practices that enhance value and efficiency.
• Indicators of Success
• 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.

Qualifications and Experience

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