3 days ago
Remote, United Kingdom or Remote, SpainSenior
Responsibilities
- Design, build, and improve reliable data pipelines, analytical models, and reusable data products for BI, internal applications, and AI consumers.
- Establish technical standards for architecture, modeling, orchestration, testing, data contracts, documentation, ownership, access control, and lifecycle management.
- Operate and evolve a governed semantic layer that provides consistent metrics and business concepts across reporting, applications, APIs, and AI-enabled services.
- Improve data operational excellence through quality controls, observability, monitoring, alerting, incident practices, performance optimization, deployment automation, and cost management.
- Deliver internal applications, APIs, automation, and governed agent interfaces such as MCP servers from discovery through operation and iteration.
- Improve dashboard deployment, authentication and authorization, access management, onboarding, and self-service workflows.
- Gather stakeholder insights, shape the product and service roadmap, and balance user value with security, maintainability, and total cost of ownership.
- Define data and service contracts with dependent teams, including ownership, interfaces, service expectations, versioning, and escalation paths.
- Mentor colleagues through pairing, technical guidance, code reviews, documentation, and reusable engineering templates.
- Evaluate and adopt relevant data, software engineering, and AI tooling practices.
Requirements
- At least 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, ELT design, pipeline performance, reliability, and maintainability.
- Deep practical experience with SQL, Python, data modeling, ELT, dbt, orchestration, and cloud data services, preferably GCP, BigQuery, dbt, and Airflow.
- Strong DevOps practices, including Git, code review, automated testing, CI/CD, infrastructure as code, environment management, and observability.
- Practical experience designing workflows for 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, including metric consistency, semantic modeling, access control, data quality, discoverability, lifecycle management, and cost, is advantageous.
- Experience implementing semantic layers, metric stores, data catalogs, or governed analytical interfaces is advantageous.
- Experience building internal applications with authentication and role-based access is advantageous.
Benefits
- The posting emphasizes a collaborative, supportive, values-driven culture focused on belonging, growth, innovation, ownership, and tangible real-world impact.
Tech Stack
Categories
Data Engineering
About Trimble
Trimble is a global technology company that connects the physical and digital worlds, transforming the ways work gets done. With relentless innovation in precise positioning, modeling and data analytics, Trimble enables essential industries including construction, geospatial and transportation. Whether it's helping customers build and maintain infrastructure, design and construct buildings, optimize global supply chains or map the world, Trimble is at the forefront, driving productivity and progress. For more information about Trimble (Nasdaq: TRMB), visit: www.trimble.com.