Customer Success Manager Super iPaaS

IBM - Charlotte, NC

Full-time

Charlotte, NC

Computer and Electronic Product Manufacturing

About the position

The Customer Success Manager at IBM is a unique role that combines technical expertise with customer-facing skills. This position is designed for individuals who can understand complex technology issues and communicate solutions effectively to clients. The CSM will work closely with key decision-makers to ensure successful adoption of IBM's integration and automation products, contributing to client retention and growth.

Responsibilities

• Understand clients' primary challenges and establish trust as a technical expert for their migration, deployment, and adoption of IBM's products.
• Lead use case exploration and business framing workshops to develop client value realization models.
• Conduct persuasive technical discussions to encourage clients to act based on their requirements and the value of IBM's solutions.
• Create post-deployment customer success plans to increase active user adoption of IBM's products.

Requirements

• Prior success in a customer-facing role such as customer success, consulting, pre-sales, or technical account management.
• Great presentation, communication, and interpersonal skills, both remote and in-person.
• Track record of achieving targets and goals/quotas.
• Self-motivated with strong organization and time management skills.
• Experience in running large, complex projects or programs.
• Ability to lead technical and in-depth conversations.
• Experience handling difficult customer situations and escalations.
• Proactive and open to working cross-functionally with sales, services, support, and other peers.
• Ability to write and analyze SQL, Java, and Python code.
• Willingness and ability to travel as required to spend time with customers.
• Business fluent in English.

Nice-to-haves

• Experience working with containers (Docker, Kubernetes) and automation (Ansible, Terraform).
• Understanding of Snowflake, Databricks, and on-premise Data Warehouse vendors.
• Familiarity with platforms and tools for large-scale data processing (HDFS, HBase, Hive, Spark, SOLR, etc.).
• Experience with large-scale cloud-based infrastructure-as-a-service platforms (Amazon AWS, Microsoft Azure, Google Cloud, OpenStack, OpenShift).
• Knowledge of Data Warehousing and Data Integration concepts and ETL/ELT tools (StreamSets, Informatica, Talend, FiveTran, SnapLogic, Pentaho, Azure Data Factory, etc.).