Our Company

Teradata is the connected multi‑cloud data platform for enterprise analytics. Our enterprise analytics solve business challenges from start to scale. Only Teradata gives customers the flexibility to handle massive and mixed data workloads—today and in the future.

Built on an open, cloud‑native, as‑a‑service architecture, Teradata Vantage enables optimal price‑performance across multi‑cloud environments and serves as the foundation for next‑generation analytics and AI workloads.

What You’ll Do

What the role is about

The Director of Product Management – Analytics Platform leads the evolution of Teradata’s analytics stack from legacy In‑Database Analytics to AI Studio‑native, Python‑first, and agentic workflows. This role owns the end‑to‑end Analytics Product Management charter, including Script Table Operator (STO), Open Analytics Framework (OAF), workload migration to AI Studio, Wisdom integration, and developer experiences such as Python notebooks.

What impact this role has

Defines how SQL, Python, and AI workflows converge into a unified developer and runtime experience
Drives a top‑priority workload migration program critical to ARR growth and renewals
Establishes STO as the execution backbone and OAF as the extensibility standard for analytics and AI

What success might look like

STO is the default execution path for advanced analytics and AI workloads
OAF is adopted as the standard packaging and extensibility framework
Enterprise customers successfully migrate from SQL‑only analytics to AI Studio workflows
Strong adoption of notebooks and Python‑first experiences versus legacy approaches

Who You’ll Work With

Product Engineering teams across India building execution, runtime, and developer tooling
Field and Worldwide Analytics Services (WWAS) teams driving customer adoption
Product Marketing (PMM) on positioning, packaging, and field enablement
Design partners and lighthouse customers shaping roadmap and architecture
Reports directly to the VP of Product and operates across global GTM stakeholders

Core Ownership Areas

Analytics Execution & Platforms

Own the strategy and roadmap for Script Table Operator (STO) as the execution bridge between SQL and external runtimes (Python/R)
Drive performance, reliability, security, and GPU‑aware execution paths
Simplify developer ergonomics, observability, and debugging across SQL and notebooks

Open Analytics Framework (OAF)

Define OAF as the standard framework to build, package, deploy, and extend analytics and AI capabilities
Enable reusable analytics components, third‑party libraries, and agentic AI “skills”
Improve versioning, dependency management, and portability across environments

In‑Database Analytics Modernization

Own lifecycle decisions on legacy analytics functions
Rationalize what remains SQL‑native versus what moves to Python, STO, and OAF
Drive convergence toward AI Studio‑native and Python‑first workflows

Workload Migration to AI Studio (Top Priority)

Lead structured migration programs from In‑DB Analytics and batch SQL to interactive and agentic workflows
Own migration tooling, reference architectures, playbooks, and success metrics
Deliver measurable improvements in time‑to‑value, adoption, and customer outcomes

Developer Experience & AI Integration

Own notebook‑based experiences inside AI Studio, competing with Databricks and Snowflake
Integrate Wisdom as a semantic and knowledge layer across structured and unstructured workflows
Reduce fragmentation across analytics, AI Studio, and developer tooling

What Makes You a Qualified Candidate (Required)

15+ years of Product Management experience in data, analytics, or platform products
Deep knowledge of SQL engines, MPP systems, and Python data ecosystems
Proven experience building or scaling execution engines and extensibility frameworks
Demonstrated success leading platform migrations and developer platforms

What You’ll Bring (Preferred)

Experience with Databricks, Snowflake (Snowpark), Spark, or similar ecosystems
Exposure to agentic AI, LLM workflows, and unstructured or vector data pipelines
Strong ability to translate complex technical systems into clear product strategy
Experience operating across India‑based engineering and US‑based GTM teams

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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.