Data Product Engineer, Data & Analytics

This is a fully remote position, open to applicants in Spain, +1 more country.

📋 Description

• Design, develop, and enhance dependable 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.

• Create and manage a governed semantic layer to ensure consistent metrics and business concepts.

• Enhance data-quality controls, observability, monitoring, alerting, incident management, performance, CI/CD, and cost management.

• Advance 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, from start to finish.

• Optimize workflows for dashboard deployment, authentication, authorization, access management, onboarding, and self-service.

• Investigate internal customer needs and translate findings into product and service roadmap priorities.

• Assist users in discovering and utilizing data products and semantic models, clearly communicating definitions, ownership, freshness, quality, limitations, and validation requirements.

• Define data and service contracts with dependent teams.

• Mentor colleagues through pairing, providing technical guidance, and conducting reviews.

• Lead the adoption of standards for modeling, testing, code review, deployment, observability, documentation, and governance.

• Assess advancements in data, software engineering, and AI tooling, and help implement practices that enhance outcomes.

⛳️ Requirements

• Over 5 years of experience in data engineering, analytics engineering, software engineering, or a related field.

• Expertise in data engineering and analytics engineering, encompassing data modeling and ELT design, pipeline performance, reliability, and maintainability.

• Extensive hands-on experience with SQL, Python, data modeling, ELT, dbt, orchestration, and cloud data services.

• Preferably experience with GCP, BigQuery, dbt, and Airflow.

• Strong DevOps practices: Git, code review, automated testing, CI/CD, infrastructure as code, environment management, and observability.

• Practical experience in designing workflows for and directing AI coding agents, as well as validating generated designs, code, tests, and documentation.

• Experience in building and maintaining production APIs, MCP servers, and endpoints.

• Ability to convey technical decisions and trade-offs to both technical and non-technical stakeholders.

• Background in BI and analytics governance, including metric consistency, semantic modeling, access control, data quality, discoverability, lifecycle management, and cost management.

• Experience in implementing semantic layers, metric stores, data catalogs, or governed analytical interfaces.

• Experience in building internal applications with authentication and role-based access.

🏝️ Benefits

• Values-driven culture focused on Belonging, Growth, and Innovation.

• Collaborative and supportive team environment.

• Opportunities for career development and driving collective growth.

• Entrepreneurial atmosphere that encourages ownership and initiative.

• Purpose-driven work that creates tangible real-world impact.

• Accommodation support during the application process.