P
$197,600 – $229,500
Listed on Protegrity’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
A senior customer success leader who guides large enterprises through modernizing their data security infrastructure and adopting AI-powered data protection solutions. This role suits technically deep professionals who thrive in complex technical sales environments and want to shape how Fortune 500 companies protect data in the AI era.
Our summary, not Protegrity’s wording. The full posting is on their site.
Skills this role names
- Amazon Bedrock
- Amazon Redshift
- Amazon Web Services (AWS)
- Apache Hadoop
- CI/CD
- Databricks
- Docker
- Google BigQuery
- IBM Db2
- Kubernetes
- LangChain
- Linux
- LlamaIndex
- Microsoft Azure
- Microsoft Windows
- PostgreSQL
- Red Hat Enterprise Linux (RHEL)
- Snowflake
- SQL
- Unix
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What they ask for
Required
- 10+ years of IT experience in customer success, data analytics, application development, or enterprise software
- At least 5 years as a technical consultant, technical project manager, solutions architect, or customer success/technical account manager
- Hands-on experience with multiple RDBMS systems and/or modern data platforms
- Strong SQL programming and scripting skills
- Solid working experience with Linux/Unix-based operating systems and Windows
- Comfortable in CLI environments
- Solid understanding of at least one major cloud platform (AWS, Azure, or GCP)
- Working knowledge of DevOps and containerization
- Demonstrated track record of retaining and growing large enterprise customers
- Multi-year, 7-figure renewal ownership
- Excellent verbal and written communication skills
- Ability to lead conversations at senior management level
- Ability to translate deep technical concepts into business outcomes
- Strong analytical and strategic thinking
- Ability to manage multiple projects and track details
- Willingness to travel up to 30-40%
- Bachelor's degree in a related field or equivalent education/experience
Nice to have
- Direct experience with data protection, privacy, or data security technologies (tokenization, format-preserving encryption, key management, DLP, data governance)
- Experience with data security platforms (Protegrity, Thales, Voltage, Immuta, BigID, Privacera, Collibra)
- Experience supporting AI/ML or GenAI workloads in production (RAG, agentic workflows, LLM guardrails, responsible-AI tooling)
- Background in highly regulated verticals (Financial Services, Insurance, Healthcare, or Retail)
- Working knowledge of PCI DSS, HIPAA, GDPR, or DORA