Analytics Solutions Analyst

ABOUT THE ROLE
The Analytics Solutions Analyst connects business strategy, analytics delivery, and data product enablement. This role combines modern business analysis, hands-on analytics development, and solution ownership to deliver trusted, actionable insights that support better decisions and measurable business outcomes.
You will partner with business leaders, Data Science Engineers, Data Engineers, and technology teams to identify high-value opportunities, shape analytics solutions, and develop minimum viable products (MVPs) or proofs of concept (POCs) that quickly validate business needs, solution feasibility, and expected value. You will use stakeholder feedback and analytical evidence to refine successful concepts into scalable, trusted analytics solutions that strengthen data adoption and enable AI-powered experiences. The role prioritizes solution ownership, KPI design, self-service enablement, and analytical problem solving, while using AI to streamline routine documentation and administrative work.
WHAT WILL YOU DO
Business Analysis & Stakeholder Consulting Using AI Coworkers and Agents
Partner with business leaders and subject matter experts to understand objectives, challenges, opportunities, and success measures.
Use AI-powered coworker tools, copilots, and agents to summarize stakeholder input, identify themes and gaps, prepare discovery questions, and accelerate follow-up actions while applying human judgment and validating outputs.
Serve as a trusted analytics advisor and use AI-assisted research and analysis to strengthen conversations about KPIs, business processes, risks, and value realization.
Translate business needs into analytics solutions, data requirements, measurable outcomes, and product enhancements, using AI to improve requirement quality, traceability, and consistency.
Create lightweight, fit-for-purpose requirements, user stories, acceptance criteria, and process documentation with AI assistance, then review and refine the content with stakeholders.
Lead workshops, design reviews, solution demonstrations, and alignment sessions, using AI-generated summaries and action tracking to improve stakeholder support and decision follow-through.
Drive consensus around KPI definitions, reporting standards, and business metrics.
Analytics & Business Intelligence Development
Design and develop MVPs, POCs, Power BI dashboards, reports, scorecards, KPI frameworks, semantic models, and reusable business metrics.
Build scalable analytics assets that support enterprise reporting and self-service analytics.
Create interactive and executive-ready visualizations that communicate trends, risks, opportunities, and performance drivers.
Develop DAX calculations, Power Query transformations, KPI logic, and business-ready semantic models.
Perform exploratory analysis using SQL, Power BI, Excel, and enterprise analytics platforms to identify patterns, root causes, and improvement opportunities.
Translate analytical findings into clear business recommendations and enable AI-powered, natural-language analytics experiences.
Data Product & Solution Ownership
Own assigned analytics products, dashboards, scorecards, and reporting solutions throughout their lifecycle.
Monitor alignment to business objectives, user adoption, stakeholder feedback, and value realization.
Define trusted KPI definitions and standardized calculations that support a single source of truth.
Prioritize enhancements based on business value, impact, adoption, and strategic alignment.
Contribute to analytics roadmaps and data product strategy in partnership with engineering and product teams.
Identify opportunities for automation, analytics modernization, process optimization, and faster decision making.
Testing, Governance & AI Enablement
Validate data accuracy, consistency, completeness, and integrity across reporting environments.
Support testing, reconciliation, root cause analysis, and issue resolution for analytics solutions and KPI calculations.
Promote reporting standards, metric governance, trusted analytics, and responsible use of enterprise data.
Maintain business KPI documentation and solution knowledge assets.
Use Microsoft Copilot, Power BI Copilot, Snowflake Cortex Analyst, and/or other enterprise AI tools to accelerate analysis and reporting development.
Apply prompt engineering fundamentals, support AI-ready semantic models, evaluate AI-generated insights, and champion responsible AI adoption.
Required Qualifications
Bachelor's degree in Business, Information Systems, Data Analytics, Computer Science, Industrial Engineering, Statistics, or a related field.
2+ years of experience in business analysis, business intelligence, analytics, reporting, or a related data role.
Hands-on experience developing Power BI reports, dashboards, and KPI scorecards, including DAX and Power Query.
Experience writing SQL queries for data analysis, testing, and validation.
Ability to gather business needs and translate them into practical analytics solutions.
Strong stakeholder engagement, communication, analytical thinking, and problem-solving skills.
Experience analyzing business processes, identifying improvement opportunities, and supporting Agile delivery and UAT.
Advanced English
Preferred Qualifications
Experience with Snowflake, Microsoft Fabric, Databricks, or equivalent analytics platforms.
Experience with semantic modeling, dimensional modeling, data warehousing, and enterprise analytics ecosystems.
Experience defining enterprise KPIs, performance scorecards, and self-service analytics programs.
Experience using Power BI Copilot, Microsoft Copilot, Snowflake Cortex Analyst, GitHub Copilot, or similar AI-enabled platforms.
Familiarity with data product management practices and Azure DevOps.
Exposure to Python, R, statistics, AI agents, MCP/API integrations, conversational analytics, or natural-language analytics design.

Employment type
Full-time

Work arrangement
Hybrid