As a Senior Principal Data Architect, provide specialized expertise to influence target state architecture and strategy, building a Data Services platform that connects scattered assurance data into one governed model.
Compensation
competitive total rewards package including base salary determined based on the role, experience, skill set and location.
Responsibilities
Own the design of the enterprise semantic model. This means stable entity identities, typed relationships, constraints and versioning across the chain Control Objective → Procedure → Application → Platform → Evidence → Finding → Closure.
Set and enforce firmwide standards for modelling, identity resolution, taxonomy and ontology.
Work with function SMEs (for example IGA and PAM) to register domain taxonomies against a common core.
Decide when to use graph-native processing and when to use lakehouse/SQL processing for traversal, impact analysis and graph analytics at scale.
Design how the semantic layer fits with the data lakehouse (Databricks bronze, silver and gold layers).
Requirements
Nice to have: risk, audit or compliance data deesign
Nice to have: identity and access management (IGA, PAM)
Lead the design, implementation, and governance of enterprise data quality and knowledge management systems to ensure accurate, trustworthy data and content for dashboards, reports, and AI tools.
Compensation
The projected compensation range for this position is $98,000.00-$163,100.00.
Responsibilities
Design and implement end-to-end data quality and data hygiene frameworks, SOPs, and quality metrics across all corporate data domains and Enterprise IT systems.
Identify, document, prioritize, and track data quality issues in a centralized issue log; partner with functional data owners to correct data in source systems and validate fixes flow through the enterprise data warehouse to downstream dashboards and reports.
Conduct regular data quality and content audits, identify root causes of data decay and knowledge silos, and partner with data engineering teams to automate quality checks and documentation workflows.
Own the enterprise knowledge management system and documentation repositories, defining the authoritative source of truth for enterprise knowledge and ensuring content is accurate, searchable, and free of duplication.
Establish and maintain a uniform framework that assigns a designated knowledge owner and point of contact to all enterprise content by functional area, including procedures for reassigning orphaned or unowned content.
Design, implement, and maintain enterprise knowledge structures, ontologies, semantic assets, metadata frameworks, knowledge graphs, and business glossaries to support analytics, AI, GenAI, semantic search, and agentic AI use cases.
Responsibilities
Develop and maintain ontologies, taxonomies, semantic models, and business glossaries
Define relationships between business concepts, policies, controls, processes, and data assets
Build and maintain enterprise knowledge graphs and semantic repositories
Translate business knowledge into AI-ready semantic structures
Support standardization of enterprise business terminology
Requirements
Bachelor's or Master's degree in Information Management, Computer Science, Data Science, Analytics, AI, or related field
Owns customer deployment, adoption, and value realization across Amplitude's digital analytics platform for emerging enterprise accounts.
Responsibilities
Own customer deployment, adoption, and outcomes for a portfolio of 30-40 accounts, from presales through renewal
Lead deployment planning and implementation across your book, including scoping, deployment plan creation, kickoff meetings, use case alignment, coordination of delivery, and project reporting
Track and manage risks and issues across active deployments, driving resolution before they impact timelines or outcomes
Monitor portfolio health through AI-augmented signals, engaging proactively to accelerate adoption, drive renewals, and deepen stakeholder engagement
Drive product adoption by running live working sessions, identifying new use cases to expand value over time, and showcasing new platform capabilities
Requirements
Nice to have: Digital analytics
Nice to have: Product analytics
Nice to have: Adjacent data/experimentation platforms
This hire must be located in the Eastern Time (EST) or Central Time Zone (CST)***
Responsibilities
Own customer deployment, adoption, and outcomes for a portfolio of 40-50 accounts, from presales through renewal
Lead deployment planning and implementation across your book, e.g.: scoping, deployment plan creation, kickoff meetings, use case alignment, coordination of delivery (e.g. managing internal and partner teams), project reporting
Track and manage risks and issues across active deployments, driving resolution before they impact timelines or outcomes
Monitor portfolio health through AI-augmented signals, engaging proactively to accelerate adoption, drive renewals, and deepen stakeholder engagement
Drive product adoption by running live working sessions, identifying new use cases to expand value over time, and showcasing new platform capabilities with a point of view on how they enable customer growth
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