At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

What You’ll Do

Help shape how enterprises turn data into trusted knowledge and context for analytics, AI and AI agents.

The Senior Manager, Knowledge & Context Architecture is a hands-on technical leadership role within Teradata's Worldwide Knowledge & Context Architecture team. You will lead architecture activities across the Americas, working with strategic customers, prospects and account teams to create practical, trusted foundations for AI.

The role combines strong foundations in data architecture, data modelling and data engineering with modern approaches to metadata, semantics, ontologies, knowledge representation, data products and agentic AI. You will work directly on important customer engagements while helping develop architecture capability across the region.

Our mission is to design the knowledge an enterprise runs on, engineer the context its AI agents need, and prove that context can be trusted. This helps make Teradata's vision for an Autonomous Knowledge Platform real for customers.

Lead Knowledge & Context Architecture activities across the Americas, working directly with strategic customers, prospects and Teradata account teams.

Act as a hands-on senior architect, leading discovery, workshops, design sessions and technical engagements.

Help customers strengthen the data foundations needed for AI, including data models, metadata, semantics, lineage, quality, governance and reusable data products.

Design architectures that bring together structured and unstructured data, metadata, business meaning and operational knowledge to provide trusted context for AI applications and agents.

Apply data architecture and modelling skills to turn business concepts, relationships, definitions and rules into usable enterprise knowledge.

Develop practical approaches for capturing and curating context, including semantic models, ontologies, industry models, metadata and AI-native data products.

Help customers assess whether context supplied to AI systems is complete, accurate, current and trustworthy.

Lead Context Engine and Knowledge Architecture workshops, deep dives and strategic proofs of concept with Americas customers.

Turn patterns from customer work into reusable architecture assets, methods, accelerators and guidance that can be used globally.

Work with the Americas field organisation to identify opportunities where Knowledge & Context Architecture can create customer value and support demand creation.

Coach architects and technical practitioners across the Americas, helping build deeper skills in data, knowledge, context and AI architecture.

Bring field evidence and customer feedback to Product Management and Engineering to help shape the Context Engine and broader platform direction.

Who you'll work with

You will be part of the Worldwide Knowledge & Context Architecture team and work closely with:

Americas Customer Solution Architects, account teams and technical leaders

Product Management and Engineering

Office of the CTO

AI Services and Consulting

Context Engine Community of Excellence

Global Knowledge & Context Architecture peers

What Makes You a Qualified Candidate

We are looking for a strong data architect who can apply that foundation to knowledge, context and AI. You do not need to have worked under every title or with every technology listed below.

Significant hands-on experience in data architecture, data modelling, data engineering or enterprise data management across complex environments.

Practical knowledge of relational data architecture, including dimensional, normalised or domain-oriented modelling approaches.

Strong practical SQL skills and confidence working directly with customer data when required.

Experience with metadata management, data catalogues, lineage, data quality or governance.

Experience designing modern data architectures spanning data warehouses, lakehouses, object storage or cloud data platforms.

Understanding of data-product concepts and how reusable, governed data assets support both human and AI consumers.

A practical understanding of modern AI architecture, which may include large language models, retrieval-augmented generation, vector search, knowledge graphs or AI agents.

Experience with semantic modelling, ontologies or knowledge representation, or the ability to apply existing data-modelling expertise to these areas.

Experience translating business requirements into clear architecture and technology decisions.

The ability to explain complex topics clearly to technical, business and executive audiences.

Experience mentoring, coaching or leading technical professionals.

What You’ll Bring

Experience designing or implementing data architectures across Teradata and complementary platforms such as AWS, Microsoft Azure, Google Cloud, Snowflake or Databricks.

Working knowledge of Python or another language used for data engineering, automation or analytics.

Experience with graph technologies, semantic technologies or knowledge graphs.

Experience using AI-assisted development, data or architecture tooling.

Experience in technology consulting, presales or another customer-facing architecture role.

Industry experience in financial services, retail, healthcare, telecommunications, manufacturing, government or another data-intensive sector.

Familiarity with enterprise architecture methods or frameworks such as TOGAF.

A degree in Computer Science, Software Engineering, Data Science or a related discipline, or equivalent practical experience.

Why We Think You'll Love Teradata

We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.

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