Lead Data Architect-Python/ Java with Cloud

Job responsibilities

• Engages technical teams and business stakeholders to discuss and propose data architecture approaches to meet current and future needs
• Defines the data architecture target state of their product and drives achievement of the strategy
• Provides architecture leadership across the data ecosystem, setting direction and making design decisions that balance scalability, resiliency, security, and cost
• Owns data architecture design and governance, including standards, reference patterns, design authority processes, and participation in data architecture governance bodies
• Executes creative data architecture solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions and break down technical problems
• Implements processes and develops tools to enhance/automate data access, extraction, and analysis efficiency
• Develops insights, methods, or tools using various analytic methods such as causal-model approaches, predictive modeling, regressions, machine learning, time series analysis, etc.
• Evaluates architectural recommendations and provides feedback on new technologies to ensure alignment with target state, standards, and strategy
• Develops secure, high-quality production code reviews and debugs code written by others identifies opportunities to eliminate or automate remediation of recurring issues to improve operational stability of applications and systems
• Leverages enterprise-authorized AI capabilities within the work environment to accelerate data architecture analysis and decisioning (e.g., option evaluation and documentation), validating outputs and handling data according to sensitivity and security requirements.

• Drives reuse-first adoption of AI-assisted data validation within SDLC/toolchain routines, improving quality checks and operational stability with traceability/auditability and resiliency expectations.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced knowledge of architecture and one or more programming languages
• Proficiency in automation and continuous delivery methods
• Built and maintained scalable APIs and services using Python (FastAPI, Flask, Django) and Java, applying clean architecture, testing, and performance tuning aligned to production SLAs.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Experienced in designing end-to-end, cloud-native systems (service decomposition, API contracts, data stores, caching, async messaging, resiliency, observability, security) and translating requirements into scalable microservices architectures deployable on Kubernetes.
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data architecture workflows with strong validation habits and awareness of data sensitivity.
• Ability to assess and validate AI-assisted data architecture recommendations before adoption, escalating uncertainty and ensuring outcomes align to resiliency, security, and auditability expectations.

• Ability to initiate and implement ideas to solve business problems
• Passion for learning new technologies and driving innovative solutions.