Forward-Deployed Customer Engineer (Enterprise)
Forward-Deployed Customer Engineer (Enterprise) at Telmai — Remote
- Company: Telmai
- Location: Remote
- Employment type: CONTRACTOR
- Salary: USD 140–160 / year
- Posted: 2026-07-17
About this role
About the Role
Telmai customers move through three stages after purchase:
Install in their VPC,
Configure data sources and catalogs,
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