Our company:

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

Why this matters (Mission & Opportunity):

• A critical new capability for this mission is the Teradata Operational & Real-Time Engine — a low-latency, high-concurrency execution layer that lets applications consume analytics at operational speed. Today, Teradata builds the insight. Tomorrow, Teradata serves it.
• This engine will close the analytics-to-action gap: insights built in VantageCloud, served to applications in single-digit milliseconds, with a single governance model across both. No more Reverse ETL. No more dual-vendor complexity. No more insights dying in the warehouse. One platform from analytics to application.

What you will do:

The Staff Product Manager for the Operational & Real-Time Engine owns the end-to-end product and business outcomes for Teradata’s real-time serving capability. This is a zero-to-one role. You will define the product, find the market, ship the first release, and build the business.

Product Strategy & Vision

• Own the product strategy for Teradata’s operational engine, including market positioning, customer segmentation, competitive differentiation, and strategic choices.
• Define the architecture: how the real-time engine integrates with VantageCloud — the serving layer, caching tier, CDC pipelines, shared governance, and unified metadata.
• Develop a clear point of view on where the OLTP + analytics boundary is heading and how Teradata wins in a world where AI agents need sub-10ms data access and applications demand operational reads on analytical data.

Discovery & Requirements

• Discover and synthesize unmet customer needs across Teradata’s Fortune 500 customer base — particularly around real-time serving, GenAI retrieval, feature stores, and application development on analytics data.
• Translate those needs into clear product requirements and specifications.
• Validate with customers early and often. Run pilots. Kill bad ideas fast.

Execution & Delivery

• Develop and own the product roadmap. Execute in close collaboration with Engineering, working across Teradata’s core platform team and the real-time engine team.
• Engage with senior engineers on deep technical topics — low-latency query paths, connection pooling, vector search integration, MCP support, caching architecture, CDC and change propagation — and guide junior engineers on product context.
• Ship with appropriate enterprise safeguards: role-based access, audit logging, encryption, and compliance controls that Teradata customers expect.

Go-to-Market

• Develop GTM strategy in close collaboration with Sales and Marketing.
• Build the narrative: why Teradata is entering the operational serving market, why now, and why it matters for customers whose analytics workloads need to become real-time applications.
• Enable field teams to sell the operational engine to existing accounts and open new doors with application development, data engineering, and AI/ML teams that Teradata has historically not reached.

Measurement & Growth

• Define and track success metrics: adoption, pilot conversion, developer engagement, workload expansion, revenue contribution.
• Use data and customer feedback to refine the product and remove friction.
• Identify expansion opportunities — GenAI serving, agent state management, real-time feature stores, vector retrieval — and sequence them into the roadmap.

Who you will work with:

• Cross-functional team including engineers, data scientists, product marketers, sales professionals, and solution architects.
• Teradata’s enterprise customer base — the world’s largest banks, telecoms, retailers, and government agencies.
• Open-source communities and ecosystem partners across database, AI/ML, and developer tooling.
• Collaborate with colleagues who share a commitment to leveraging AI responsibly, ensuring our people and customers benefit from the opportunities AI creates.

What makes you a qualified candidate:

• 8+ years of product management experience, with demonstrated track record of shipping complex technical products and building successful businesses.
• Strong understanding of the OLTP and real-time serving market. Experience with low-latency database architectures, operational data stores, or real-time analytics systems.
• Deep technical ability — you can read an architecture diagram, review a query plan, reason about caching layers, and hold your own with database engineers.
• Demonstrated drive to ship in close collaboration across engineering, design, sales, and marketing.
• Experience with zero-to-one or early-stage product development within a larger company.
• Excellent communication skills — you can present to a CTO and write a PRD with equal clarity.

What you will bring:

• Experience with real-time data serving systems — operational databases, feature stores, caching tiers, or low-latency query engines.
• Familiarity with GenAI application architectures — RAG pipelines, agent frameworks (LangChain, LlamaIndex), MCP, vector search, embedding retrieval.
• Understanding of CDC, streaming, data integration, or data platform architectures.
• Background in enterprise or developer-facing platforms.
• Experience with competitive dynamics in the database and analytics market (Snowflake, Databricks, AWS, Google Cloud). 

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