Analytics Engineer

• Independently develop Bronze → Silver dbt models following established standards
• Contribute to Gold-layer models and analytics outputs under guidance
• Apply dimensional modeling concepts, including facts and dimensions, for analytics and BI use cases
• Build, test, and document analytics models using dbt
• Refactor models to improve clarity, performance, or consistency
• Apply reusable patterns and macros where appropriate
• Implement dbt data quality tests, including not-null, uniqueness, and accepted-values tests
• Validate data outputs against business logic and expected behaviour
• Identify and resolve potential data quality issues with peers
• Monitor model performance, warehouse costs, model runs, failures, and anomalies
• Work with analysts and stakeholders to understand reporting and data requirements
• Communicate progress, risks, and blockers proactively
• Own dbt documentation for delivered models and columns
• Contribute to team documentation, standards, and playbooks
• Suggest improvements to models, tests, and workflows
• Support junior engineers through knowledge sharing or informal guidance

• Own product analytics across different product lines
• Define and track success metrics and targets aligned with Product and Company strategy
• Craft data stories that guide product leaders in critical decisions
• Collaborate with engineers to develop reusable, scalable data products
• Define event instrumentation and taxonomy practices for event-driven architecture and self-service analytics
• Enable Product and GTM teams on event instrumentation and insight generation
• Increase data literacy and empower teams to self-serve insights
• Evaluate and apply LLMs and AI tooling to accelerate query generation, dashboard building, and insight synthesis
• Connect product usage to commercial outcomes such as win/loss, expansion, and renewal
• Scale repeatable analyses and automations
• Partner with Product Managers, Designers, Engineering, and Go-to-Market teams

Senior Product Analytics Engineer

• Manage and adjust pay ranges regularly
• Manage job families and sub-families, regularly reviewing their application
• Manage the annual compensation cycle with the Head of Compensation and Benefits
• Act as the first-level escalation point for compensation queries
• Maintain accurate, complete, accessible, and responsibly managed workforce data
• Maintain a data playbook following implementation of the new HRIS
• Work with People Operations to ensure data accuracy through a core calendar and monitoring system
• Provide training to new People Operations team members
• Prepare regular and ad-hoc HR reports for the CPO and senior stakeholders
• Maintain a regular reporting calendar
• Develop dashboards and visualizations using Power BI, Excel Power Query, advanced pivots, and HR system dashboards
• Analyze trends and provide actionable insights
• Define data-management roles, responsibilities, and policies
• Develop data-management cycles and corporate-intelligence playbooks
• Understand stakeholder data needs and interdepartmental dependencies
• Collaborate with HR Business Partners and Talent teams
• Present findings clearly to non-technical stakeholders
• Identify opportunities to automate reporting and improve data workflows
• Support implementation of HR technology, AI, and analytics tools
• Continually improve the compensation review process and related communications
• Report to the Head of Compensation & Benefits within the Compensation & Benefits Centre of Excellence

Analytics Engineer jobs in Portugal

Analytics Engineer

Senior Product Analytics Engineer

Compensation and Data Analytics Specialist