Senior Analytics Engineer – AI, Business Intelligence

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Yuxi Global powered by Veritas Automata

WebsiteLinkedInAll Job Openings

201 - 500 employees

Yuxi Global (powered by Veritas Automata) is a leading people and technology force multiplier dedicated to empowering businesses in achieving their digital goals since 2005. We specialize in providing comprehensive solutions, including turnkey enterprise-grade application, managed development teams and strategic consulting via our Veritas Automata Services Team, tailored to meet the unique requirements of our clients. We are headquartered in the United States and operate with a robust team of over 150 skilled IT professionals located strategically in North and South America, including the United States, Colombia, Mexico, Brazil, and Costa Rica.

📋 Description

• Own end-to-end analytics initiatives from stakeholder discovery through implementation, validation, automation, and business adoption. • Partner with business, BI, data, and technical stakeholders to clarify objectives, define success metrics, and convert ambiguous requests into actionable analytics work. • Design, write, optimize, and validate advanced SQL queries against large-scale enterprise datasets. • Develop scalable analytics solutions that support operational decision-making, product insights, root-cause analysis, and recurring business reporting. • Apply AI and automation to improve BI workflows, including natural language-to-SQL, BI copilots, automated insight generation, anomaly/root-cause workflows, and data-quality monitoring. • Build, evaluate, test, and refine AI-assisted analytics workflows to ensure accuracy, explainability, repeatability, and business trust. • Identify opportunities to reduce manual reporting effort, streamline stakeholder requests, improve analytical throughput, and increase BI team productivity. • Validate analytical outputs through rigorous data-quality checks, metric reconciliation, source-of-truth review, and stakeholder confirmation. • Collaborate with BI engineers, data engineers, product analysts, and business stakeholders to align data models, metric definitions, and reporting logic. • Create clear documentation for analytics logic, SQL assumptions, data lineage, AI workflow behavior, known limitations, and stakeholder-facing outputs. • Operate independently in a fast-paced environment with limited onboarding support, while proactively identifying risks, dependencies, blockers, and decisions needed. • Communicate insights, tradeoffs, risks, and recommendations clearly to both technical and non-technical stakeholders. • Support adoption of analytics and AI-enabled BI solutions by training stakeholders, gathering feedback, measuring usage, and iterating on workflows. • Help define reusable patterns for agentic BI delivery, including evaluation methods, validation checklists, governance practices, and automation playbooks. • Mentor analysts or engineers on advanced SQL, AI-assisted analytics workflows, business framing, and end-to-end project ownership.

🎯 Requirements

• 8+ years of professional experience in business intelligence, analytics engineering, data analytics, product analytics, data engineering, or related fields. • Advanced SQL expertise, including experience working with large, complex, enterprise-scale datasets. • Experience analyzing datasets at significant scale, ideally involving hundreds of millions of rows or similarly complex data environments. • Demonstrated ability to own analytics projects end-to-end, from stakeholder requirements and problem framing through implementation, validation, delivery, and adoption. • Hands-on experience applying AI, automation, or agentic workflows to analytics, reporting, data quality, or decision-support use cases. • Experience with one or more AI-enabled BI patterns such as natural language-to-SQL, BI copilots, automated insight generation, root-cause analysis, anomaly detection, data-quality monitoring, or analytics workflow automation. • Strong understanding of data validation, metric reconciliation, source-of-truth alignment, and data-quality practices. • Ability to work independently, ramp quickly, and drive outcomes without heavy day-to-day management oversight. • Strong stakeholder management skills, including the ability to clarify ambiguous requests, challenge assumptions, and guide business users toward better analytical questions. • Strong written and verbal communication skills in English. • Bachelor’s degree in Computer Science, Data Analytics, Statistics, Information Systems, Engineering, Business Analytics, Mathematics, Economics, or equivalent practical experience.

🏖️ Benefits

• Employees can work remotely