• Sales Support & Technical Leadership: Partner with the sales team to drive the technical aspects of the sales cycle. Lead discussions around Data Discovery, DSPM, and cloud security, and present tailored security solutions to prospective clients.
• Customer Focus: Use a deep understanding of industry best practices to help customers navigate complex situations and achieve optimal outcomes. Ensure that solutions are not only technically sound but also aligned with their broader business objectives, fostering long-term partnerships and delivering measurable value.
• Cloud Security Expertise: Provide technical leadership in securing cloud environments, including AWS, Azure, GCP, and Oracle, focusing on data protection, regulatory compliance, and cloud infrastructure security.
• Data Architecture: In-depth knowledge of enterprise data architecture, data privacy, and security technologies.
• SaaS Application Security: Advise customers on best practices for securing SaaS applications and ensure that their cloud applications meet security and compliance standards.
• Data Access & Governance: Lead discussions around Data Access Controls, Compliance (GDPR, HIPAA, PCI-DSS), and Data Governance best practices to ensure clients’ data security and regulatory requirements are met.
• Technical Presentations & Demos: Conduct product demos, POCs, and presentations to clearly communicate the value of security solutions to both technical and non-technical stakeholders.
• Collaboration & Relationship Building: Work cross-functionally with engineering, product management, and customer success teams to ensure successful implementation of security solutions and maintain strong client relationships.
• Value Delivery: Collaborate closely with post-sales teams to ensure that customers fully realize the value of their investments by effectively implementing and optimizing solutions.

Required Qualifications

• Technical Expertise in Data Discovery: Experience defining and implementing Data Discovery policies, including various techniques such as REGEX, Patterns, Dictionaries, Keywords and Exact Data Matching.
• Operational Proficiency with Cloud Infrastructure: Hands-on experience with cloud infrastructure, specifically AWS, Azure, GCP, and Oracle including identity and access management (IAM), and cloud security best practices.
• Experience with DSPM: Strong knowledge of Data Security Posture Management (DSPM) and its application in cloud environments.
• SaaS Security: Experience in securing SaaS applications and providing guidance on how to apply security best practices in cloud-based applications.
• Data Governance & Compliance: Understanding of Data Access Controls, Data Governance, and compliance frameworks such as GDPR, HIPAA, and PCI-DSS.
• Data Systems: Operational experience with one or more of the following data systems: MongoDB, Cassandra, DynamoDB, HDFS, Hive, HBase, AWS S3, DynamoDB, Redshift, Azure file and blob storage, etc.
• Linux & Kubernetes: Proficiency in Linux and Networking, with experience in containerized environments using Kubernetes is a plus.
• Sales Engineering Experience: Proven experience in a Sales Engineer or Pre-Sales Engineer role, with a strong ability to engage with both technical and non-technical stakeholders.
• Effective Communication Skills: Strong verbal and written communication skills, with the ability to articulate complex technical solutions clearly to a diverse audience. Outstanding presentation, communication, and interpersonal skills.

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Preferred Qualifications

• Successful Sales Engineering track record with a minimum of 5+ years pre-sales engineering or consulting role focusing on medium and large enterprise accounts.
• Bachelor's degree in a technical field or a related discipline.
• Relevant industry certifications with a focus on cloud or security such as AWS Fundamentals, Azure, GCP, CISSP, CISM or similar.
• Experience with security tools and platforms focused on data protection, cloud security, and compliance. Expertise in CASB (Cloud Access Security Brokers), SASE (Secure Access Service Edge), and DLP (Data Loss Prevention) technologies and their business applications.
• Strong technical acumen with the ability to comprehend & communicate intricate technical concepts.
• Experience in designing, developing, and refining RAG (Retrieval-Augmented Generation) models.
• Knowledge of vector databases and indexing methods to store and retrieve information for conversational contexts.

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