Leads the data engineering squad in Data Enablement for AI, setting engineering and modelling standards and building enterprise data products consumed by ML and AI teams.
The role remains hands-on in SQL and Python, owns the datamart and data product roadmap with Product Owners, partners with Data Platforms, Architecture, Data Science and Governance teams, and turns ML outputs into business intelligence.
With a strong focus on Corporate and SME Banking data.

Job Overview:

Data Engineering Leadership & Strategy: Set data engineering standards, medallion design patterns and delivery practices that enable scalable, reusable data products across Group Digital & AI.
Hands-on Engineering: Design, build and optimise complex SQL on Amazon Redshift and Microsoft SQL Server (stored procedures, views, materialized views, functions) and Python pipelines on AWS.
ML & AI Enablement: Deliver feature-ready datasets for ML and AI teams and use model outputs to create business intelligence for Corporate and SME Banking.
Data Modelling & Architecture Standards: Define dimensional modelling standards (star schema, SCDs) and conformed enterprise models that integrate multiple data sources at enterprise function level.
Platform Collaboration: Partner with Data Platforms and Architecture teams on AWS services, orchestration and CI/CD to ensure performant, secure and cost-efficient data products.
Data Quality, Governance & Controls: Embed data quality checks, lineage, access controls and documentation to meet data governance standards and CBUAE regulatory requirements.
Squad Leadership & People Development: Lead, hire and mentor the data engineering squad, conduct code reviews and drive delivery performance, capability building and agile ways of working.

Required:

15 years of experience in Data Engineering and Data Warehousing.
Solid industry experience in banking, working with Corporate and SME Banking data.
Hands-on experience with AWS and Amazon Redshift.
Proven experience leading a data engineering team or squad.
Experience delivering medallion-based data products and datamarts for ML and AI consumption.
Bachelor's Degree in Computer Science, Engineering, Information Technology or related discipline; Master's Degree preferred.
AWS Certification (Data Engineer or Solutions Architect) preferred.

Director, Data Engineering

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