Trimble Inc.
Trimble Inc.
Trimble Inc. is a technology company developing software, hardware, and data-driven solutions for construction, transportation, geospatial, and natural resources. Its tools combine precise hardware with real-time data and connected workflows to help professionals coordinate projects, manage complex operations, and improve efficiency across field and office environments. Trimble serves organizations and specialists working in industries where accurate information, collaboration, and operational visibility are essential.

Data Product Engineer, Data & Analytics — Spain Remote

Build governed data products, semantic layers, and AI-enabled workflows at Trimble. Support transportation and logistics technology through resilient analytics engineering.

Description

  • Build and enhance reliable data pipelines, analytical models, and reusable data products for BI, internal applications, and AI consumers.
  • Set standards for architecture, modeling, orchestration, testing, data contracts, documentation, ownership, access control, and lifecycle management.
  • Develop and operate a governed semantic layer that keeps metrics and business concepts consistent.
  • Strengthen data quality, observability, monitoring, alerting, incident response, performance, CI/CD, and cost controls.
  • Advance AI-enabled development practices for coding agents and assess their generated designs, code, tests, and documentation.
  • Document architectural decisions, dependencies, operational knowledge, and business context for colleagues and AI agents.
  • Build internal applications, APIs, automation, and governed agent interfaces such as MCP servers from design through operation.
  • Streamline dashboard deployment, authentication, authorization, access management, onboarding, and self-service workflows.
  • Investigate internal customer needs and convert findings into product and service roadmap priorities.
  • Help users find and use data products and semantic models by explaining definitions, ownership, freshness, quality, limitations, and validation needs.
  • Establish data and service contracts with dependent teams.
  • Support colleagues through pairing, technical coaching, and code and design reviews.
  • Drive adoption of standards for modeling, testing, code review, deployment, observability, documentation, and governance.
  • Assess advances in data, software engineering, and AI tools and help introduce practices that improve results.

Requirements

  • At least five years of experience in data engineering, analytics engineering, software engineering, or a related field.
  • Advanced expertise in data and analytics engineering, including data modeling, ELT design, pipeline performance, reliability, and maintainability.
  • Strong hands-on experience with SQL, Python, data modeling, ELT, dbt, orchestration, and cloud data services.
  • Experience with GCP, BigQuery, dbt, and Airflow is preferred.
  • Strong DevOps capability across Git, code review, automated testing, CI/CD, infrastructure as code, environment management, and observability.
  • Practical experience designing workflows for AI coding agents and validating their generated designs, code, tests, and documentation.
  • Experience developing and operating production APIs, MCP servers, and endpoints.
  • Ability to explain technical decisions and trade-offs to both technical and non-technical stakeholders.
  • Experience with BI and analytics governance, metric consistency, semantic modeling, access control, data quality, discoverability, lifecycle management, and cost management.
  • Experience implementing semantic layers, metric stores, data catalogs, or governed analytical interfaces.
  • Experience developing internal applications with authentication and role-based access control.

Benefits

  • A values-led culture built around Belong, Grow, and Innovate.
  • A collaborative and supportive team environment.
  • Opportunities to develop your career and contribute to shared growth.
  • An entrepreneurial workplace that encourages ownership and initiative.
  • Purpose-driven work with tangible real-world impact.
  • Support with accommodations during the application process.

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