Job Description:
- Role Overview
- The ST of Data Engineering AI Platforms will lead the design development and delivery of scalable data engineering platforms that power analytics AI ML and intelligent decisioning across the bank
- This leader will own the end to end data engineering strategy spanning modern data platforms cloud data architecture and AI ready data pipelines while providing hands on technical leadership to teams of data engineers and platform engineers
- This role sits at the intersection of data engineering database architecture and applied AI ensuring data products are reliable scalable secure and optimized for advanced analytics and AI use cases across consumer and commercial banking
Key Responsibilities:
- Data Engineering Architecture
- Serve as a hands on technical leader in the design of scalable data pipelines data stores and information flows across the enterprise
- Design and optimize cloud based big data platforms including ingestion transformation storage and consumption layers
- Lead the engineering of ETL ELT frameworks streaming pipelines and batch processing solutions
- Conduct enterprise wide assessments of data stores and data flows to identify bottlenecks friction points and modernization opportunities
- Own data modeling standards to ensure alignment with business objectives performance and accessibility
- AI Enablement Advanced Analytics
- Enable and support AI ML and GenAI initiatives by building reliable high quality and well governed data pipelines
- Collaborate with Data Science teams to operationalize models including feature engineering pipelines inference data flows and model monitoring data
- Support AI driven use cases such as predictive analytics recommendations NLP based insights and intelligent automation
- Stay current with market trends embed innovative practices into strategy and drive the organization forward with an AI first approach ensuring AI initiatives move beyond proof of concept to enterprise scale solutions
- Approach data engineering with an AI mindset and vice versa reflecting the evolving and inseparable nature of the two disciplines
Technical Requirements:
- Desired Qualifications
- Experience in financial services with understanding of consumer and commercial banking data
- Experience supporting or enabling AI ML and GenAI solutions including feature pipelines and analytics platforms
- Familiarity with data visualization and BI tools Tableau Cognos SAS
- Knowledge of responsible AI data governance and regulatory considerations in highly regulated environments
- Experience modernizing legacy data platforms into cloud native architectures
- Executive speaking skills ability to articulate strategy challenge the status quo and present to senior leadership and key stakeholders with confidence
- Experience working across or within highly collaborative non hierarchical organizational cultures with an emphasis on peer relationships and open communication
Preferred Skills:
Technology->AI-Generative AI->Generative AI - Basic,Technology->Data Engineering->Databricks