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Responsible for   :

1. Data Architecture & Pipeline Oversight

• Design and maintain scalable, secure, and efficient data pipelines (ETL/ELT).
• Ensure integration of different data sources into centralized platforms (e.g., data lakes, warehouses).
• Prioritize data request based on impact, feasibility, and resource availability.

 2. Technical Leadership

• Guide the team in adopting best practices for data modeling, transformation, and storage.

• Evaluate and implement tools (e.g., ADF, Azure Database, Logic Apps) and cloud platforms (Azure,Open Source).

• Lead performance tuning and optimization of data workflows.

• Continuous learning in banking and related system’s data structures, reporting tools and etc...

 3. Data Governance & Quality

• Implement data quality checklist/SOP, validation checks.

• Monitor data integrity across core banking modules (e.g., GL, customer, account, transaction).

• Lead reconciliation efforts between source systems and reporting outputs.

 4.  Team Management & Development

• Recruit, mentor, and manage data engineers.
• Conduct performance reviews, set goals, and foster continuous learning.
• Promote a collaborative and innovative team culture.

5.  Cross-Functional Collaboration

• Work closely with product, Finance, BO, Cards, Corporate, EChannel and IT teams.
• Translate business requirements into technical specifications.

6.   Mandatory Requirements:

• Familiarity with the banking/finance domain, ATM and Cards, Digital, Corporate Channels systems
• Proven experience with Azure Cloud Platform, particularly:
  • Azure Data Factory
  • Azure Synapse
  • Azure Database
  • Azure Storage Account
  • Logic Apps
  • Dataflow
• Strong understanding of data integration, ETL/ELT processes, and data modeling.
• Proven track record in building and scaling enterprise-grade data platforms.
• Databases: Relational (Oracle, SSMS, PostgreSQL), NoSQL (MongoDB)
• Data Warehousing & Lakehouse architectures

7. Preferred Qualifications:

• Experience with:
  • Apache Airflow
  • Apache Spark
  • Docker
  • Kubernetes
• Knowledge of CI/CD practices and DevOps tools is advantageous.

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or related fields.
• Additional qualifications or certifications in Cloud Data Engineering, Database Management, or Big Data Technologies are highly desirable.
• experience in data engineering, data management, or regulatory reporting roles.
• leadership or managerial capacity overseeing data teams or reporting units.
• Proven experience in financial services sector 
• Strong background in  Cloud Platform and data architecture design.