Forward-Deployed Customer Engineer (Enterprise)

About the Role

Telmai customers move through three stages after purchase:

1. Install in their VPC,
2. Configure data sources and catalogs,
3. Adopt profiling, monitors, and automated validation.

This role is responsible for accelerating all three for large enterprise customers. You will be the technical owner who ensures Telmai is deployed, integrated, and delivering value fast.

What You’ll Do

Implementation & Activation

• Guide customers through automated deployment in AWS, Azure, or GCP
• Provide hands-on cloud/network/security support when needed
• Integrate Telmai with customer ecosystems (GCS, S3, ADLS; BigQuery, Snowflake, Databricks; Atlan, Alation, Collibra; Iceberg, Delta, Hudi)
• Configure assets, profiling, rules, lineage, and validation flows
• Build small utilities or synthetic datasets to speed onboarding

Data Reliability Outcomes

• Enable automated validation across landing → transform → consumption layers
• Diagnose issues such as schema drift, null spikes, volume anomalies, invalid values, or rule failures
• Work with engineering, analytics, governance, and business teams to align on quality goals
• Demonstrate improvements in data reliability and trust

Customer Leadership

• Run workshops, stand-ups, and weekly sessions
• Navigate enterprise org structures and unblock cross-team dependencies
• Communicate clearly with both technical and executive stakeholders
• Act as the primary technical owner for post-sales success

Influence Product

• Bring deployment insights back into product and engineering
• Inform roadmap areas (validation automation, lakehouse integrations, AI-agent workflows)
• Help build playbooks and best practices for future implementations

What We’re Looking For

Background & Skills

• 4–6 years in a customer-facing engineering role (FDE, SA, CE, consulting engineer)
• Strong data architecture and pipeline fundamentals
• Hands-on cloud experience (AWS, GCP, or Azure)
• Experience with lakehouse/warehouse ecosystems
• Familiarity with data lakes, cloud storage, catalogs, or metadata systems
• Comfortable leading multi-stakeholder enterprise conversations

Traits & Mindset

• AI-first and highly adaptable
• Customer-obsessed and outcome-driven
• High ownership, bias for action, and low-ego collaboration
• Comfortable with ambiguity and fast-moving startup environments

Nice-to-Haves

• Experience with DQ/observability or metadata platforms
• Iceberg/Delta/Hudi familiarity
• Python/SQL for quick utilities
• Exposure to regulated industries (FSI, healthcare, insurance)

Why Join Telmai

• Founding impact: Help shape Telmai’s customer engineering function
• High visibility: Work directly with the founders
• Enterprise momentum: Deploy Telmai at brands like McDonald’s and Fortune 500s
• AI + Data inflection point: Build on top of Telmai’s new Data Reliability Agent
• Low bureaucracy: High trust, fast decisions, real ownership

Interview Process

Intial meeting with hiring manager to understand interest and technical skills

Meeting with Sales Engineer for customer management skills

Interview with both founders and small working exercise.