Data Product Engineer, Data & Analytics

Trimble Inc.

. Design, build, and improve reliable data pipelines, analytical models, and reusable data products for BI, internal applications, and AI consumers .

Posted 10/7/2026full-timeRemote • Spain, United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering and analytics engineering, focusing on data modeling, ELT design, and pipeline performance. Proficient in building reliable data products, APIs, and implementing governance standards for data quality and access control.

Highest-signal resume keywords

Data EngineeringAnalytics EngineeringSQLPythonDevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingELT DesignPipeline PerformanceData QualityAutomationAPI DevelopmentSemantic ModelingGovernance StandardsIncident ManagementCost Management

Soft Skills

Technical CommunicationMentoringCollaboration

Tools & Technologies

GCPBigQueryDbtAirflowGitCI/CDInfrastructure as Code

Industry Keywords

Business IntelligenceData GovernanceAccess ControlLifecycle ManagementData Catalogs

Tech Stack

Tools & technologies

AirflowBigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design, build, and improve reliable data pipelines, analytical models, and reusable data products for BI, internal applications, and AI consumers
Establish standards for architecture, modeling, orchestration, testing, data contracts, documentation, ownership, access control, and lifecycle management
Shape and operate a governed semantic layer for consistent metrics and business concepts
Improve data-quality controls, observability, monitoring, alerting, incident practices, performance, CI/CD, and cost management
Evolve AI-native practices for coding agents and review generated designs, code, tests, and documentation
Make architectural decisions, dependencies, operational knowledge, and business context accessible to colleagues and AI agents
Deliver internal applications, APIs, automation, and governed agent interfaces such as MCP servers end to end
Improve workflows for dashboard deployment, authentication, authorization, access management, onboarding, and self-service
Research internal customer needs and translate insights into product and service roadmap priorities
Help users discover and consume data products and semantic models, communicating definitions, ownership, freshness, quality, limitations, and validation requirements
Define data and service contracts with dependent teams
Mentor colleagues through pairing, technical guidance, and reviews
Guide adoption of standards for modeling, testing, code review, deployment, observability, documentation, and governance
Evaluate developments in data, software engineering, and AI tooling and help adopt practices that improve outcomes

Requirements

What you’ll need

5+ years of experience in data engineering, analytics engineering, software engineering, or an adjacent field
Mastery of data engineering and analytics engineering, including data modeling and ELT design, pipeline performance, reliability, and maintainability
Deep practical experience with SQL, Python, data modelling, ELT, dbt, orchestration, and cloud data services
Preferably experience using GCP, BigQuery, dbt, and Airflow
Strong DevOps practices: Git, code review, automated testing, CI/CD, infrastructure as code, environment management, and observability
Practical experience designing workflows for and directing AI coding agents, and validating generated designs, code, tests, and documentation
Experience building and maintaining production APIs, MCP servers, and endpoints
Ability to communicate technical decisions and trade-offs to 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 building internal applications with authentication and role-based access

Benefits

Comp & perks

Values-driven culture centered on Belong, Grow, and Innovate
Collaborative and supportive team culture
Opportunities to build a career and drive collective growth
Entrepreneurial environment with ownership and initiative
Purpose-driven work with tangible real-world impact
Accommodation support during the application process