Senior Principal Data Analyst

Heredia, Costa Rica

About the Role

The Senior Principal Data Analyst will serve as a strategic analytics partner, leveraging complex business, operational, and learning datasets to generate meaningful insights and support leadership decision-making.

This position will lead executive reporting, establish performance measurement frameworks, oversee data quality and governance, and develop predictive analyses. The primary focus is to improve operational efficiency and provide visibility into the effectiveness of customer, partner, and employee enablement initiatives.

Key Responsibilities

Lead the development, enhancement, and ongoing maintenance of executive dashboards, performance scorecards, and recurring business reports.
Collaborate with business leaders to establish and monitor key performance indicators (KPIs), ensuring standardized definitions, measurement criteria, and performance benchmarks.
Conduct advanced analytical assessments, forecasting, and predictive modeling to identify emerging trends, potential risks, business opportunities, and their impact.
Design and optimize Tableau dashboards and business intelligence solutions, leveraging Snowflake and other authorized enterprise data platforms.
Establish and maintain data governance standards, including data definitions, quality controls, lineage, documentation, and reporting consistency.
Partner with program management, product, customer-facing, and enablement teams to evaluate how learning initiatives influence workforce readiness, adoption rates, and overall business performance.
Present analytical findings, business implications, and strategic recommendations to senior leadership, while conducting ad hoc analyses to support business decisions.
Explore and implement AI-driven automation to streamline recurring reporting, data preparation, and validation activities, measuring improvements and eliminating inefficient manual processes.
Incorporate AI-supported analytical approaches while ensuring data accuracy, validating assumptions, maintaining privacy standards, and applying appropriate human oversight.
Take on additional responsibilities as required.

Required Qualifications and Experience

Bachelor’s degree or equivalent relevant professional experience.
At least 7 years of experience in data analytics, business intelligence, business analysis, or a related discipline.
Advanced proficiency in SQL, business intelligence platforms, data visualization, and Microsoft Excel.
Proven experience building executive-level dashboards, establishing KPIs, and converting complex datasets into actionable insights and recommendations for senior management.
Strong capabilities in data governance, quality assurance, analytical modeling, stakeholder management, and business communication.
Ability to assess AI-generated insights critically, validate underlying assumptions, and identify potential risks related to data accuracy, privacy, and handling.

Preferred Qualifications

Hands-on experience with Tableau, Snowflake, and enterprise-level data environments.
Background in predictive modeling, forecasting, statistical analysis, or data governance practices.
Experience evaluating learning and development programs, employee enablement, customer adoption, or operational effectiveness through data.
Exposure to AI-powered analytics solutions and the implementation of automated reporting processes.

AI & Continuous Learning

Leverage AI tools to improve exploratory analysis, data documentation, and reporting processes while independently verifying outputs and safeguarding confidential information.
Demonstrate consistent use of AI in daily activities, including practical examples of how these technologies have transformed existing workflows rather than simply reducing execution time.
Critically assess AI-generated results for accuracy, potential bias, privacy concerns, and appropriate data usage, recognizing when human judgment and intervention are necessary.
Explore and evaluate both internal Cornerstone AI solutions and external technologies, sharing recommendations with the team and discontinuing tools or processes that no longer provide value.
Maintain professional and technical knowledge through industry communities, certifications, practical experimentation, and continuous learning, while sharing relevant insights with colleagues.

Working Style & Core Competencies

Customer-Centric Mindset: Prioritize understanding learner needs and business challenges before selecting or implementing technological solutions.
Innovation & Transformation: Challenge existing practices, identify opportunities for improvement, and replace outdated tools or processes with more effective alternatives.
Proactive Leadership: Anticipate potential challenges, take ownership of emerging issues, and drive solutions independently.
Execution & Accountability: Deliver results, evaluate performance, and continuously refine solutions based on measurable outcomes.
Strategic Vision: Stay informed about evolving business priorities and technological advancements to anticipate future organizational needs.
AI-Driven Mindset: Integrate AI into everyday work to rethink and optimize processes, going beyond its use as a productivity shortcut.
Comfort with Ambiguity: Take ownership of complex, unfamiliar challenges, navigate uncertainty, and remain committed to finding effective solutions.

To apply for this job please visit recluta.org.