Digital S/W Engineering Product Lead Analyst, Vice President

Description

This is a strategic role for someone who tracks developments in their field and judges how they apply to their own work and to the business.

You own the engineering scope that supports the enterprise data privacy strategy and the data risk and control framework and taxonomy.

You will lead planning, discovery and rollout of the data privacy governance policy and its related risk controls.

You will lead build-or-buy decisions, set integration architecture (APIs, data flows, identity and access, security controls), run the product backlog, and drive adoption of privacy-enhancing technologies across global business lines.

The ideal person combines solid software engineering with agile product management, deep knowledge of global privacy laws such as GDPR, CCPA/CPRA and LGPD, and extensive experience running complex third-party vendor products for the company.

Responsibilities

• Serve as the lead subject matter expert on privacy by design, automated data discovery, consent management, data subject requests and data lineage.
• Support key data privacy initiatives across the organization as a subject matter expert.
• Lead product discovery: gather business needs and requirements, run build-or-buy analysis, document and communicate findings, and map them to data governance and data risk control standards.
• Evaluate architecture and build-or-buy options for incoming SaaS platforms, checking fit with enterprise microservices, AWS/GCP cloud and hybrid environments.
• Work with enterprise architecture, information security and core engineering to design resilient, scalable, secure APIs, webhooks, event-driven pipelines and data sync flows.
• Coach engineering squads on consuming and building RESTful APIs, data mapping, identity integration (OAuth2, SAML, OIDC) and telemetry and observability.
• Give hands-on guidance on automating privacy checks in CI/CD pipelines, SDK integration, and synthetic or masked data generation.
• Turn regulatory frameworks, data governance policies and data risk taxonomies into technical user stories, epics and acceptance criteria.
• Keep milestones on track, report delivery risks early, and manage roadmap and milestone changes.
• Own requirements, detailed roadmaps, and the full lifecycle of metrics and report production.
• Assess risk in business decisions with attention to the firm's reputation and to its clients and assets, drive compliance with laws, rules and policy, use sound ethical judgment, and escalate and report control issues openly.
• Work with architects and product managers to define system architecture that is scalable, resilient and secure.

Requirements

• Recommended: 6+ years in data governance, data product management, engineering or a related area, with banking or finance experience preferred.
• Recommended: Hands-on software development in at least one server-side language, such as Java or Python.
• Recommended: Proven work with RESTful APIs, microservices, distributed systems and integration middleware such as Kafka, MQ and API gateways.
• Recommended: Solid grasp of cloud-native tools (Kubernetes/OpenShift, AWS/GCP, Docker) and security protocols (OAuth 2.0, SAML, mTLS).
• Recommended: Detailed knowledge of global data privacy laws, including GDPR, CPRA, CCPA and others.
• Recommended: Strong knowledge of data structures, algorithms and software design patterns.
• Recommended: Proficiency in Excel, PowerPoint, JIRA, Confluence and SharePoint.
• Recommended: Communicates clearly with different audiences, builds consensus, influences at all levels, and works well with others toward shared goals.
• Recommended: Expertise in data governance frameworks, metadata management, automated data discovery, classification and DSAR workflows.
• Recommended: Deep experience in SaaS lifecycle governance, including vendor evaluation, integration architecture, security reviews, SLA monitoring and contract or license tracking.
• Recommended: Balances efficient processes with continuous improvement, sees the big picture and still checks the details.
• Recommended: Understands systems and management processes, and knows where to find and how to interpret information.
• Recommended: Working knowledge of data operating models, data governance, and data compliance and security laws within large financial services firms.
• Recommended: A bachelor's or university degree; a master's degree is preferred.

Conditions

This is a full-time position in the Digital Software Engineering job family, within the Technology group.

The primary location salary range is $120,800 - $170,800.

Automated tools, including AI, may be used to match candidates' skills to roles, but people make all hiring decisions.

The company is an equal opportunity employer.