Customer Solutions Architect
Teradata · Seoul, South Korea
- Грейд
- Senior
- Формат
- Офис
- Категория
- Архитектор
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Customer Solutions Architect
Our Company
Teradata is the trusted AI and knowledge platform that connects data, business context, and AI so organisations can move from insight to real-time action across cloud, on-premises, and hybrid environments. We work with many of the world's largest enterprises across banking, retail, manufacturing, healthcare, and the public sector, including leading organisations throughout APJ.
What You'll Do
Own the technical relationship for a portfolio of strategic enterprise accounts, maintaining an up-to-date Tech Vision for each account that connects current architecture, target state, customer priorities, adoption risks, and the path to measurable business value.
Identify and progress expansion opportunities, including new workloads, additional capacity, AI Studio adoption, Enterprise Vector Store use cases, and consolidation of analytics environments onto Teradata. Lead technical discovery, solution design, sizing, demonstrations, benchmarks, workshops, and cloud readiness activities.
Increase adoption of available platform capabilities by translating customer use cases into practical architectures, proofs of concept, technical points of view, ecosystem diagrams, and business value summaries tailored to engineering and executive audiences.
Partner with account teams to connect technical recommendations to commercial outcomes, supporting opportunity qualification, configuration, quoting, provisioning, SITEID setup, network requirements, entitlement alignment, retention, and ARR expansion.
Represent the voice of the customer by communicating product feedback, capability gaps, competitive insights, and field observations to Teradata product and engineering teams. Success is measured by account retention, expansion, platform adoption, and trusted executive relationships, not by tickets closed.
Who You'll Work With
Operate within a POD, a focused cross-functional team of sales, presales, and customer success professionals aligned to a defined group of accounts or market segment.
Serve as the primary technical voice in the POD, partnering closely with the POD Sales Lead on commercial priorities and with product, engineering, services, cloud, and customer success teams on solution delivery and adoption.
Report directly to the CSA Team Lead for the assigned territory or region, with a dotted-line relationship to the POD Sales Lead. The CSA Team Lead provides technical direction, career development, and cross-territory alignment.
What Makes You a Qualified Candidate
Eight or more years of experience in a technical, customer-facing role such as solution architecture, presales, or delivery, working with enterprise data platforms or cloud analytics.
Demonstrated success managing and growing existing enterprise accounts, with measurable results in retention, expansion, platform adoption, and executive stakeholder relationships.
Practical experience with AWS, Microsoft Azure, or Google Cloud, plus familiarity with hybrid cloud data architecture and enterprise workload requirements.
Strong knowledge of enterprise data warehouse architecture, including parallel processing, columnar storage, SQL, query performance tuning, workload management, and solution sizing based on data volumes, concurrency, and performance targets.
Experience working with enterprise customers in APJ across one or more of Australia, Japan, ASEAN, Korea, or Taiwan. A degree in computer science, software engineering, mathematics, data science, or a related field is preferred; equivalent professional experience will also be considered.
What You'll Bring
A practical understanding of retrieval-augmented generation architecture, embedding models, similarity search, vector stores, and how these capabilities connect to large language model workflows in enterprise environments.
Experience using AI Studio or a comparable platform in customer demonstrations or proofs of concept, with the ability to position Enterprise Vector Store against specific customer use cases.
Confidence using SQL and Python during hands-on customer sessions, demonstrations, benchmarks, and technical workshops.
Understanding of the enterprise sales process, including qualification, technical scoping, ecosystem integrations, solution sizing, configuration, cloud readiness, licensing, consumption models, and commercial quoting support.
Knowledge of the competitive landscape, open-source technologies, and Google BigQuery, with the ability to articulate where Teradata provides differentiated value.
Clear communication across technical and business audiences, with the ability to produce high-quality proposals, technical summaries, architecture diagrams, customer briefings, and executive-level points of view.
Disciplined portfolio management, including keeping account status current, identifying underused capabilities, and escalating technical or adoption risk before it becomes a commercial issue.
Industry knowledge in one or more priority sectors is advantageous: financial services, retail and consumer goods, public sector and government, or manufacturing and supply chain, including the relevant analytics, governance, sovereignty, procurement, seasonality, or operational requirements.
#LI-MM1
Required Skills
Required Languages
🇬🇧 English
Our Company
Teradata is the trusted AI and knowledge platform that connects data, business context, and AI so organisations can move from insight to real-time action across cloud, on-premises, and hybrid environments. We work with many of the world's largest enterprises across banking, retail, manufacturing, healthcare, and the public sector, including leading organisations throughout APJ.
What You'll Do
Own the technical relationship for a portfolio of strategic enterprise accounts, maintaining an up-to-date Tech Vision for each account that connects current architecture, target state, customer priorities, adoption risks, and the path to measurable business value.
Identify and progress expansion opportunities, including new workloads, additional capacity, AI Studio adoption, Enterprise Vector Store use cases, and consolidation of analytics environments onto Teradata. Lead technical discovery, solution design, sizing, demonstrations, benchmarks, workshops, and cloud readiness activities.
Increase adoption of available platform capabilities by translating customer use cases into practical architectures, proofs of concept, technical points of view, ecosystem diagrams, and business value summaries tailored to engineering and executive audiences.
Partner with account teams to connect technical recommendations to commercial outcomes, supporting opportunity qualification, configuration, quoting, provisioning, SITEID setup, network requirements, entitlement alignment, retention, and ARR expansion.
Represent the voice of the customer by communicating product feedback, capability gaps, competitive insights, and field observations to Teradata product and engineering teams. Success is measured by account retention, expansion, platform adoption, and trusted executive relationships, not by tickets closed.
Who You'll Work With
Operate within a POD, a focused cross-functional team of sales, presales, and customer success professionals aligned to a defined group of accounts or market segment.
Serve as the primary technical voice in the POD, partnering closely with the POD Sales Lead on commercial priorities and with product, engineering, services, cloud, and customer success teams on solution delivery and adoption.
Report directly to the CSA Team Lead for the assigned territory or region, with a dotted-line relationship to the POD Sales Lead. The CSA Team Lead provides technical direction, career development, and cross-territory alignment.
What Makes You a Qualified Candidate
Eight or more years of experience in a technical, customer-facing role such as solution architecture, presales, or delivery, working with enterprise data platforms or cloud analytics.
Demonstrated success managing and growing existing enterprise accounts, with measurable results in retention, expansion, platform adoption, and executive stakeholder relationships.
Practical experience with AWS, Microsoft Azure, or Google Cloud, plus familiarity with hybrid cloud data architecture and enterprise workload requirements.
Strong knowledge of enterprise data warehouse architecture, including parallel processing, columnar storage, SQL, query performance tuning, workload management, and solution sizing based on data volumes, concurrency, and performance targets.
Experience working with enterprise customers in APJ across one or more of Australia, Japan, ASEAN, Korea, or Taiwan. A degree in computer science, software engineering, mathematics, data science, or a related field is preferred; equivalent professional experience will also be considered.
What You'll Bring
A practical understanding of retrieval-augmented generation architecture, embedding models, similarity search, vector stores, and how these capabilities connect to large language model workflows in enterprise environments.
Experience using AI Studio or a comparable platform in customer demonstrations or proofs of concept, with the ability to position Enterprise Vector Store against specific customer use cases.
Confidence using SQL and Python during hands-on customer sessions, demonstrations, benchmarks, and technical workshops.
Understanding of the enterprise sales process, including qualification, technical scoping, ecosystem integrations, solution sizing, configuration, cloud readiness, licensing, consumption models, and commercial quoting support.
Knowledge of the competitive landscape, open-source technologies, and Google BigQuery, with the ability to articulate where Teradata provides differentiated value.
Clear communication across technical and business audiences, with the ability to produce high-quality proposals, technical summaries, architecture diagrams, customer briefings, and executive-level points of view.
Disciplined portfolio management, including keeping account status current, identifying underused capabilities, and escalating technical or adoption risk before it becomes a commercial issue.
Industry knowledge in one or more priority sectors is advantageous: financial services, retail and consumer goods, public sector and government, or manufacturing and supply chain, including the relevant analytics, governance, sovereignty, procurement, seasonality, or operational requirements.
#LI-MM1
Required Skills
Required Languages
🇬🇧 English
- aws
- google_cloud
- google_bigquery
- microsoft_azure
- python
- sql
- ai_studio
- enterprise_vector_store
- rag
- embedding_models
- vector_store
- llm
Оценка вакансии
64/100 · удовлетворительно
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- Зарплата не указана
- Компания и проект описаны
- Контакта нет
- Стек описан подробно
- Формат работы понятен
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