Lead Data Engineer

Trimble Inc.•US - Remote, TX, TX

3d•$136,400 - $187,500•Onsite

About The Position

The Lead Data Engineer will own Document Crunch's end-to-end data platform and serve as the organization's primary data champion within Trimble's hub-and-spoke operating model. This is a hands-on technical leadership role responsible for modernizing the Document Crunch data estate, aligning it to Trimble enterprise standards, and enabling trusted analytics, product telemetry, operational reporting, and AI-powered decision support. The role combines deep data engineering execution with cross-functional leadership. The successful candidate will build and operate production data systems while partnering closely with Document Crunch Product and Engineering, go-to-market leaders, and the central Trimble Data Team. The position is expected to influence architecture and standards broadly without requiring an initial people-management mandate.

Requirements

Hands-on technical leadership role
Deep data engineering execution
Build and operate production data systems
Partnering closely with Document Crunch Product and Engineering, go-to-market leaders, and the central Trimble Data Team
Influence architecture and standards broadly
Modernizing the Document Crunch data estate
Aligning it to Trimble enterprise standards
Enabling trusted analytics, product telemetry, operational reporting, and AI-powered decision support
Migration from Redshift to Snowflake
Build and maintain ingestion pipelines, warehouse models, transformation layers, orchestration, data contracts, and deployment workflows using warehouse-as-code practices
Implement standardized telemetry on priority Document Crunch product and data pipelines
Integrate Document Crunch CRM and operational data into Trimble DX and relevant enterprise master-data processes
Map Document Crunch data into Trimble processed-layer and Customer 360 master entities
Partner with central teams on Master Data Management pilots, survivorship rules, account cleansing, identity resolution, and reconciliation
Define scalable dimensional, domain, and semantic data models
Implement layered data-quality controls through dbt tests, business-rule validation, orchestration-level asset checks, and pipeline alerting
Integrate enterprise observability capabilities
Set service expectations for data freshness, reliability, completeness, and recovery
Onboard Document Crunch metadata into the enterprise catalog
Establish a practical business glossary, ownership model, and lineage standards
Document business logic, metric definitions, data contracts, and source-of-truth decisions
Partner with Security, Privacy, Legal, and enterprise Data Governance teams to apply appropriate access controls, retention practices, and policy requirements
Own the strategy and technical foundation for executive dashboards and self-service analytics
Evaluate and rationalize BI tools, data products, and reporting workflows
Enable product managers and business teams to answer routine questions independently
Develop the data and semantic foundation for conversational analytics, AI agents, natural-language querying, and AI-assisted dashboard creation
Align Document Crunch orchestration and agent capabilities with Trimble strategies
Build or integrate secure interfaces
Serve as Document Crunch's primary technical and operational contact for the Trimble Data Team
Translate central standards into practical implementation plans for Document Crunch
Surface product-specific requirements back to enterprise teams
Lead cross-collaboration workshops, architecture reviews, roadmap alignment, and knowledge exchange
Codify the Document Crunch integration into a reusable, code-driven M&A Data Integration Playbook

Responsibilities

Own the technical architecture and roadmap for Document Crunch data systems in alignment with business priorities and Trimble enterprise standards.
Lead the migration from Redshift to Snowflake as the unified enterprise cloud data platform, including source assessment, target design, migration sequencing, validation, and cutover.
Build and maintain ingestion pipelines, warehouse models, transformation layers, orchestration, data contracts, and deployment workflows using warehouse-as-code practices.
Establish patterns that are maintainable, observable, secure, and reusable across teams and future integrations.
Implement standardized telemetry on priority Document Crunch product and data pipelines to produce reliable product-usage data.
Integrate Document Crunch CRM and operational data into Trimble DX and relevant enterprise master-data processes.
Map Document Crunch data into Trimble processed-layer and Customer 360 master entities, including Account, Opportunity, Support, and related domain models.
Partner with central teams on Master Data Management pilots, survivorship rules, account cleansing, identity resolution, and reconciliation.
Define scalable dimensional, domain, and semantic data models that support analytics, operational reporting, and AI consumption.
Implement layered data-quality controls through dbt tests, business-rule validation, orchestration-level asset checks, and pipeline alerting.
Integrate enterprise observability capabilities, including table freshness, volume anomalies, schema drift, lineage, and incident response.
Set service expectations for data freshness, reliability, completeness, and recovery.
Onboard Document Crunch metadata into the enterprise catalog and establish a practical business glossary, ownership model, and lineage standards.
Document business logic, metric definitions, data contracts, and source-of-truth decisions for both human and AI-agent consumption.
Partner with Security, Privacy, Legal, and enterprise Data Governance teams to apply appropriate access controls, retention practices, and policy requirements.
Own the strategy and technical foundation for executive dashboards and self-service analytics across revenue, marketing, customer success, product, and operations.
Evaluate and rationalize BI tools, data products, and reporting workflows to reduce duplication and inconsistent metrics.
Enable product managers and business teams to answer routine questions independently while preserving governed definitions and access controls.
Develop the data and semantic foundation for conversational analytics, AI agents, natural-language querying, and AI-assisted dashboard creation.
Align Document Crunch orchestration and agent capabilities with Trimble strategies such as Snowflake Cortex Search, Cortex Agents, and enterprise NLP frameworks.
Build or integrate secure interfaces—including MCP-style services where appropriate—that allow approved AI systems to discover and use governed data assets.
Serve as Document Crunch's primary technical and operational contact for the Trimble Data Team.
Translate central standards into practical implementation plans for Document Crunch and surface product-specific requirements back to enterprise teams.
Lead cross-collaboration workshops, architecture reviews, roadmap alignment, and knowledge exchange with Data Ops, Analytics, Product, Engineering, and GTM stakeholders.
Codify the Document Crunch integration into a reusable, code-driven M&A Data Integration Playbook.