Senior Product Marketing Manager - StreamSets, Data and AI, Software
IBM
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.
Your Role and Responsibilities
- In the role, you will drive the outcome of connecting differentiated POVs with the right buyers and experts, measured by new signings, retention rates, average customer value, absolute and trend NPS, market segment share, win loss rate, analyst ranking, and social influence.
- Act as the market catalyst for the IBM StreamSets offering, providing guiding views on key problems, competitors, and differentiators grounded in data
- Identify opportunities, distinctive competencies, and positioning for IBM StreamSets
- Translate technology into marketing messages and compelling stories that influence analysts, customers, and partners towards IBM’s offerings
- Act as the launch linchpin that galvanizes internal support across all channels and drives demand for the offerings
- Stay active in customer conversations at events or in the field and online
- This is a Hybrid role, attendance to the office will be required only 3 times per week.
Required Technical and Professional Expertise
- Experience in Product or B2B Marketing
- Experience creating marketing business plans
- Interest in, but not limited to, the following software products: generative AI, hybrid cloud, data and analytics, security, supply chain, or sustainability
- Experience working and communicating with groups of different backgrounds and skills to enable collaboration
- Experience managing multiple priorities at once, prioritizing tasks, and shifting in an environment of continuous change.
Preferred Technical and Professional Expertise
- Deep understanding of go-to-market strategies
- Experience developing audience strategies (e.g., understanding and prioritizing potential audiences based on key behaviors/characteristics)
- Client experience design & measurement (e.g., using technology to measure and improve the customer experience and translate data into meaningful actions).