Product Analyst-Portugal (Remote)

DoiT is a global technology company specializing in cloud solutions that combine data, technology, and human expertise to help customers operate in scalable, well-architected environments. They deliver DoiT Cloud Intelligence, integrating advanced technology with human intelligence to solve complex multicloud problems and drive efficiency. The company has expertise in Kubernetes, GenAI, CloudOps, and partners strategically with AWS, Google Cloud, and Microsoft Azure, serving over 4,000 customers worldwide.

• 5+ years of experience in product analytics or related roles with digital product teams.
• Practical understanding of AI's impact on analytics workflows; experience accelerating insight generation and safe AI operationalization.
• Systems thinker with a track record building scalable systems.
• Builder mindset with ambition to create processes, systems, and paths where none exist.
• Ability to operate in ambiguity, prioritize independently, and collaborate across teams.
• Clear communicator with experience presenting analysis to product managers and business stakeholders.
• Strong analytical foundation with advanced SQL skills.
• Experience with event-based analytics tools such as Mixpanel, Looker (or similar BI tools), Segment, and dbt.
• Preferred familiarity with public cloud environments (AWS, GCP, Azure), FinOps/cloud cost management, and enterprise SaaS concepts.

1. Product Measurement & Instrumentation:

• Partner with Engineering to define and maintain event taxonomy, tracking standards, and instrumentation quality.
• Build and maintain scalable, self-service dashboards for product teams.
• Establish and document clear metric definitions.
• Contribute to improving measurement as the product evolves.
• Leverage AI to unlock insights and recommendations.

2. Analytics & Data Foundations:

• Work within product analytics stack (e.g., Mixpanel, Segment, Looker) to ensure accurate reporting.
• Build and maintain dbt models for core product entities and behaviors.
• Contribute to a clean, usable metric layer for stakeholders.
• Structure and analyze Voice of the Customer inputs (support, churn, NPS, sales feedback, interviews).
• Support data quality through testing, monitoring, documentation, and automation.
• Deploy AI tooling to enhance data differentiation.

3. Insight Generation & Reporting:

• Deliver recurring product analytics reporting (adoption, engagement, retention).
• Provide analytics readouts with clear findings and recommendations.
• Analyze links between product behavior and revenue/retention.
• Support automated reporting and AI-assisted workflows.
• Strive for automated and self-service insights, aided by AI techniques.