Technical Customer Success - ETL / Data Lake /

My client is looking for a Technical Customer Success Manager, who will own the post-sale technical relationship for enterprise customers across the group's products — including data protection and lifecycle management (backup, archive, recovery, replication, and consumption of application data), enterprise AI enablement, workflow automation, large-scale document management, and service and sales operations optimisation.

You will be the trusted technical advisor who ensures customers implement successfully, adopt deeply, and realise measurable value — while feeding customer insight back into product and engineering.

Location

Greater Boston preferred. Atlanta considered.

The Impact You Will Have

• Onboarding & Implementation
• Adoption & Value Realisation
• Technical Advisory
• Retention & Growth
• Cross-Functional Collaboration

The Product Suite

The platform is designed to help customers protect their Salesforce data, manage it through its full lifecycle, and turn that same dataset into value faster. As Technical Customer Success Manager, you will support customers across the following product suite:

• Salesforce & other Data Replication
• Backup and Restore
• Data Archive
• Time Machine
• Data Lake / Data Lakehouse
• API Integration to Snowflake, Databricks and others
• Observability

What We Look For

• 5-8+ years in Technical Customer Success, Solutions Consulting, Implementation, or Technical Account Management within enterprise SaaS.
• Proven track record owning the technical relationship for a portfolio of enterprise/mid-market accounts, driving adoption, renewal, and expansion.
• Strong grasp of data management concepts: backup and recovery, archiving, replication, and data lifecycle management.
• Experience guiding customers through integrations with cloud data platforms and BI tools.
• Excellent stakeholder management — equally comfortable in a technical working session and an executive business review.

Tech Stack Familiarity

• Salesforce core objects, metadata, and multi-org architecture; AppExchange-listed applications (a plus)
• AWS (including S3-based data lakes and AWS Marketplace-distributed solutions).
• Microsoft Azure (including Azure-based deployments and Azure Marketplace).
• Heroku for platform-hosted application components.
• Snowflake and Databricks for AI-ready data activation and lakehouse architectures.
• Google BigQuery and Amazon Athena for query-in-place analytics.
• Amazon Redshift and Azure Synapse as enterprise data warehouse destinations.
• Tableau and other BI tools consuming continuously replicated SaaS application data.

Please note: ONLY USA Nationals or Green Card holders will be considered.