Develops and maintains the enterprise data platform’s semantic layer, ensuring business data is consistent, discoverable, and reusable across analytics and AI applications.
Design, develop, and maintain conceptual, logical, physical, dimensional, and semantic data models aligned with enterprise architecture standards and business requirements.
Translate business concepts into reusable models that define entities, attributes, relationships, business rules, KPIs, and standardized definitions.
Map business concepts to underlying data assets and maintain semantic metadata to support analytics, generative AI, RAG, natural language querying, and AI agents.
Collaborate with Enterprise Architecture, data engineering, governance, analytics, AI teams, and business stakeholders to validate definitions and align models with enterprise standards.
Improve semantic consistency, metadata completeness, and contextual relevance to enhance data quality and AI application outcomes.
Requirements
Bachelor’s degree in Computer Science, Information Systems, Data Management, or a related discipline
Design and implement data governance frameworks and target operating models for clients, ensuring compliance with GDPR, EU AI Act, and data security standards.
Responsibilities
Design and implement data governance frameworks and target operating models
Define data roles, responsibilities, and processes
Conduct workshops with client stakeholders
Translate regulatory requirements into practical policies
Build governance into technical setup with data catalogs, quality, lineage, and access management
The AI Governance Lead enables NYPA's responsible AI transformation by combining governance, risk management, and data governance disciplines to accelerate AI adoption safely and effectively.
Compensation
The estimated salary range for this position is: $134,000 - $168,000.
Responsibilities
Lead meetings and working groups to develop, maintain, and implement Authority wide AI governance policies, standards of practice, and risk management processes.
Ensure integration and enforcement of AI governance principles throughout the AI use case lifecycle, from initial intake and assessment to deployment and ongoing monitoring.
Evaluate departmental AI usage and requests, partnering with IT and business stakeholders to guide proposals through approval, development, and operationalization.
Maintain a comprehensive inventory of AI systems, models, and use cases using designated AI governance tools and technologies.
Manage AI governance and risk projects, including control assessments and data readiness evaluations, to ensure data quality and compliance for AI implementation.
Lead global data product development for Supply Chain and Procurement, combining end-to-end supply chain expertise with hands‑on data engineering.
Compensation
We offer competitive salaries, aligned with local market benchmarks and the specific scope and responsibilities of each role. Compensation is determined based skills relevant to the position, education and/or training. We are committed to fair and equitable pay practices in accordance with applicable laws and regulations.
Responsibilities
Translate procurement and supply chain requirements into clear, buildable data‑product designs
Design, develop, test, and maintain data pipelines, analytical data models, semantic models, dashboards, and data‑quality controls
Assess source‑system data and identify quality, availability, lineage, and integration issues
Build prototypes and critical solution components directly
Define engineering standards, testing requirements, documentation, and technical acceptance criteria
Requirements
University degree in Computer Science, Data Engineering, Information Systems, Supply Chain Management or a related technical field
Design, develop, and maintain scalable cloud-based data pipelines and engineering solutions for the Department of Veterans Affairs Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services program.
Responsibilities
Design, develop, and maintain scalable data ingestion and processing pipelines using Azure Data Factory, Azure Databricks, Apache Kafka, and related cloud technologies.
Engineer and optimize data lakehouse solutions, including Delta Lake architectures, semantic models, conformed dimensions, and partitioning strategies that support enterprise analytics and AI/ML workloads.
Integrate data from enterprise systems, legacy platforms, and cloud-based sources using batch, streaming, and event-driven ingestion patterns.
Implement automated data validation, reconciliation, and monitoring to ensure data accuracy, completeness, consistency, and freshness.
Support migration of data pipelines and analytical workloads to Summit, validating parity with source systems and ensuring production readiness.
Requirements
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline
Nice to have: supporting VA or other federal agency data modernization initiatives
Nice to have: Microsoft Azure Government cloud environments
Seeking a Business Systems Analyst with strong expertise in payments data analysis, transaction processing, reconciliation and data‑driven business insights.
Responsibilities
Gather and document business requirements related to payments data and reporting
Analyze payment transaction data to identify trends, anomalies and process improvement opportunities
Perform data mapping, data profiling and data validation across multiple systems
Support reconciliation, settlement and exception management activities
Define reporting and dashboard requirements for business stakeholders
Lead data governance and transformation initiatives within the C‑AFC Data Office, driving delivery of data management, compliance and regulatory projects across financial services.
Responsibilities
Manage end‑to‑end delivery of data management, governance and transformation workstreams
Develop and maintain delivery plans, coordinate activities across business, technology, data and change teams
Analyze business and regulatory requirements, document current‑state processes, identify gaps and translate requirements into solutions
Apply analytical thinking to complex data, governance and delivery challenges
Support implementation and ongoing operation of data governance requirements
Help shape how Xero manages data as a strategic asset and govern AI responsibly, enabling teams to innovate with confidence and customers to trust the company.
Locations (4)
Melbourne, Victoria, Australia
Sydney, New South Wales, Australia
Auckland, Auckland, New Zealand
Wellington, Wellington, New Zealand
Responsibilities
Evolving Xero’s privacy, data and AI governance frameworks to enable rapid, responsible data use and AI adoption and deployment across the business
Partnering with cross-functional teams to translate governance policies and requirements into practical, user-friendly guidance at scale and support their adoption
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