Introduction
At IBM, we believe technology shapes the world. We're a catalyst for that innovation. We're driving change that improves businesses, society, and the human experience. Our Marketing, Communications & Corporate Social Responsibility (MCC) team tells this story. We shape IBM's brand, capture attention in the market, and share our perspective with clients, partners, the media, and fellow IBMers. On our team, you'll work with bright, collaborative minds who bring passion and creativity to everything they do. You'll be part of a culture built on openness, trust, and teamwork. Where your ideas matter and your growth is supported. Join us and help bring innovation to life.
Your Role And Responsibilities
We are building a small, elite AI strike team embedded in the Marketing, Communications, and CSR (MCC) Strategy & Operations team. The mission is to move fast, explore what's possible with agentic and conversational AI, and prove value quickly—before anything is scaled or productionized elsewhere.
This team operates as a rapid-action unit focused on experimentation, learning, and proof-of-value rather than long-term platforms or production systems.
In this role, you enable speed. You provide just-enough data pipelines and integrations to ensure AI experiments can move forward quickly and credibly.
THIS ROLE IS
- A speed enabler for AI and automation experimentation
- Focused on data readiness, access, and feasibility
- Embedded in a small, elite delivery team
- Optimized for rapid iteration
THIS ROLE IS NOT
- A long-term data platform ownership role
- A heavy governance or compliance function
- A traditional BI or reporting role
Key Responsibilities
- Build fast, flexible data pipelines to support AI POCs
- Integrate marketing, operational, and enterprise data sources
- Assess data quality, availability, and limitations early
- Identify data blockers that could prevent feasibility
- Collaborate closely with AI Engineers on workflows and models
- Make pragmatic tradeoffs between speed and structure
- Refactor quickly as experiments evolve
Preferred Education
Master's Degree
Required Technical And Professional Expertise
- Strong background in data engineering and data transformation
- Solid SQL and Python skills
- Experience integrating data across systems and domains with an understanding of data storage solutions that enable efficient processing and retrieval.
- Exposure to performing batch or real-time processing on collected data, with knowledge of serving data via APIs for querying purposes.
- Experience working with database integration, including addressing problems associated with handling messy, unstructured data sets.
- Experience working with ensuring data is properly processed and served to meet the needs of data scientists and other stakeholders.
- Strong technical judgment in fast-moving environments
Preferred Technical And Professional Experience
- Experience supporting AI or ML workloads
- Familiarity with marketing or GTM datasets
- Experience in POC-heavy environments
