Data Engineer, VP
NatWest Group (company site, opens in a new tab)ChennaiOn-siteDirect career pageEst. 35–60 LPA
Posted on 23 Sept
Reach people at NatWest Group
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at NatWest Group you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Develop and maintain advanced data engineering pipelines, focusing on automation and scalable architecture to support business and customer needs.
- Apply innovative data-driven solutions including data modeling, ETL design, and streaming data ingestion aligned with the strategic data platform and streaming strategy.
- Manage cost-effective data platform operations while ensuring secure and compliant handling of customer and bank data, incorporating AI agent architecture and integration within enterprise systems.
Minimum Requirements
- Work Experience Required: Not explicitly mentioned in the JD, but role is at Vice President level indicating senior experience expected.
- Strong expertise in AI agent architecture and engineering including components like planning loops, RAG, prompt engineering, and output validation.
- Proficiency in programming languages and foundational knowledge in data and software engineering fundamentals.
- Experience with cloud-native infrastructure management, MCP servers/clients, microservices, CI/CD pipelines, secure production-grade AI application deployment, and compliance mechanisms.
Ideal Candidate Profile
- Senior-level data engineer with proven ability to deliver complex, cost-optimized data solutions aligned to enterprise strategic objectives and customer-focused outcomes.
- Experience driving engineering excellence through technical leadership, framework development, automated testing, and governance in AI and data engineering contexts.
- Comfortable engaging with diverse stakeholders to translate complex business problems into scalable, secure, and innovative data architectures and solutions.