Description

What's the Job?

• Shape modern data architecture across cloud and on-prem environments in a large-scale banking ecosystem, designing scalable patterns for application, analytics, workflow, and AI-enabled workloads.
• Act as an advisor to senior leadership by developing the architectural framework and delivery approach for highly complex business and technical needs across multiple groups.
• Lead strategy and resolution of unique, enterprise-wide challenges through deep evaluation across technical domains, delivering long-term, large-scale solutions.
• Define and influence transformation architecture by describing current state, target state, and transition plans, including cutover strategies and investment planning.
• Ensure adherence to established standards, policies, methodologies, and industry best practices while mentoring teams and communicating architecture decisions to both technical and business stakeholders.

What's Needed?

• 7+ years of experience in data architecture, data engineering, database platforms, or enterprise technology roles, with significant experience in large-scale financial services or banking environments.
• 7+ years of designing enterprise-scale data architectures across hybrid cloud, public cloud, private cloud, and on-premises platforms.
• 7+ years of experience with relational, NoSQL, columnar, distributed, and shared-nothing database technologies.
• Strong ability to design scalable architectures using partitioning, sharding, replication, workload isolation, horizontal scaling, and distributed processing patterns.
• Hands-on capability with technologies such as SQL, Python, Java, Spark, Kafka, Airflow, APIs, and modern data pipeline frameworks.

What's in it for me?

• Opportunity to drive enterprise data modernization with measurable value, balancing innovation with scalability, cost (TCO), and ROI considerations.
• Role influence across strategic tool selection, architecture frameworks, and reusable design patterns that enable teams to move faster with guardrails.
• Chance to mentor senior technologists and guide architecture decisions that impact secure, resilient, and future-ready data platforms.
• Work on AI-aware data architecture patterns, including how AI/ML workloads interact with enterprise data platforms.
• Collaborate across diverse systems and stakeholders to translate constraints into forward-looking architectures and practical implementation blueprints

Key Skills

Education

Any Graduate