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Job Description

Role Overview:

A leading financial services organisation is seeking a senior technology leader to lead enterprise-wide data and artificial intelligence engineering and delivery. The role will own the development of secure, scalable data pipelines, reusable data products, and production-ready data capabilities supporting business applications, advanced analytics, and artificial intelligence initiatives.

Key Responsibilities:

- Lead the enterprise data and artificial intelligence engineering function, including capability development, engineering standards, and delivery practices.

- Build and scale secure, reusable data pipelines, transformations, and data products to support business applications, analytics, and artificial intelligence outcomes.

- Establish engineering excellence through Agile, DevOps, DataOps, automation, and standardised delivery frameworks.

- Own end-to-end delivery, prioritisation, and execution across multiple engineering teams and workstreams.

- Partner with architecture, data governance, artificial intelligence portfolio teams, platform teams, and business stakeholders to align delivery with enterprise strategy.

- Ensure data quality, lineage, observability, security, privacy, and regulatory compliance across engineering outputs.

Ideal Candidate Profile:

- 20 - 28 years of experience in technology and engineering, with substantial leadership experience in enterprise data engineering and delivery.

- Strong banking or financial services background, with an understanding of financial data, fraud detection, and credit scoring.

- Demonstrated experience building and scaling enterprise data platforms, reusable data products, and large-scale data pipelines.

- Deep understanding of modern data architectures, including data lakes, data warehouses, lakehouse architecture, data fabric, streaming, and data mesh.

- Strong exposure to cloud-based data platforms, artificial intelligence and machine learning data enablement, and modern engineering practices.

- Proven ability to lead large engineering teams, manage complex delivery portfolios, and translate strategic priorities into production-ready solutions.

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