Principal Data Architect Chief Data Office

About the role

This role shapes modern data architecture across cloud and on-prem environments in a large-scale banking ecosystem. The ideal candidate designs scalable patterns for application, analytics, workflow, and AI-enabled workloads while guiding the evolution of legacy systems.

Responsibilities

• Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering products and solutions that are long-term, large-scale, and require vision, creativity, innovation, advanced analytical and inductive thinking.
• Translate current-state constraints into forward-looking architectures.
• Drive solutions that balance innovation with measurable value, including considerations of scalability, cost (TCO), and ROI.
• Work across diverse systems, define architectural patterns, and enable teams to modernize data environments with practical, AI-aware solutions.
• Mentor teams, align architecture to business outcomes, and communicate effectively with both technical and business stakeholders.

Requirements

• 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.

Qualifications

• Proven ability to design scalable architectures using partitioning, sharding, replication, workload isolation, horizontal scaling, and distributed processing patterns.
• Experience architecting batch, streaming, event-driven, real-time, near-real-time, and API-based data integration patterns.
• Strong understanding of how application workloads, analytical workloads, reporting workloads, workflow engines, and AI/ML workloads interact with enterprise data platforms.
• Hands-on capability with technologies such as SQL, Python, Java, Spark, Kafka, Airflow, APIs, and modern data pipeline frameworks.
• Expertise in data modeling, including conceptual, logical, physical, dimensional, canonical, domain-driven, and event-based models.
• Strong knowledge of data security architecture, including encryption, tokenization, masking, access controls, entitlement models, secrets management, and audit logging.
• Ability to define and evaluate non-functional technical requirements, including latency, throughput, scalability, availability, resiliency, recovery, observability, security, and maintainability.
• Experience developing reference architectures, reusable design patterns, platform standards, technical guardrails, and implementation blueprints.

Skills

• Deep expertise in distributed data systems, application and workflow integration, and analytic platforms.
• Ability to translate current-state constraints into forward-looking architectures.
• Strategic engagement with all levels of professionals and managers across the enterprise.
• Effective communication with both technical and business stakeholders.
• Ability to drive solutions that balance innovation with measurable value.

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement