Senior Data Analyst - Data Intelligence

Saputo; Dallas (TX); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Saputo is seeking a Senior Data Analyst, Data Intelligence, to partner with Finance, Sales, Operations, and other business areas. You will translate questions into actionable insights while designing data structures, automated workflows, datasets, and semantic layers for trusted reporting and scalable analytics.

The role requires strong business acumen, advanced SQL skills, and the ability to bridge business stakeholders with technical teams to improve data quality, reporting efficiency, and

Qualifications

• Bachelor's degree in Finance, Economics, Business Analytics, Data Science, Information Systems, Computer Science, Engineering, Mathematics or Statistics.

Responsibilities

• Define reporting requirements, KPIs, analytics use cases, and success measures with Finance, Sales, Ops and stakeholders.
• Translate business questions into analyses, communicating findings, assumptions, limitations and actions.
• Identify trends, anomalies, gaps, and opportunities in data to surface insights beyond standard reporting.
• Support planning, forecasting, variance analysis, and executive reporting with high-quality data.
• Create dashboards, reports, datasets and models for cross-functional teams to evaluate scenarios.

Skills

Advanced SQL

Data analytics

Business acumen

Stakeholder comms

Data visualization

Education

Bachelor's degree in a quantitative field

Tools

Power BI

SQL

Microsoft Fabric

Python

SAP data

Job description

At Saputo, we bring good to the table by making high-quality products, investing in our people, and supporting communities around the world . As a top 10 global dairy processor, we value contributions that matter and strive to foster an inclusive, growth-driven work environment. Ready to bring your best?

The Senior Data Analyst, Data Intelligence will serve as a hybrid analytics and technical resource supporting Finance, Sales, Operations, and other business functions. Reporting to the Sr. Manager, Data Intelligence, this role will translate business questions into actionable insights while also designing and maintaining the data structures, automated workflows, curated datasets, and semantic layers needed to support trusted reporting and scalable analytics. The role requires strong business acumen, advanced SQL and analytical skills, and the ability to bridge business stakeholders with technical teams to improve data quality, reporting efficiency, and decision support.

How you will make contributions that matter...

Business Analytics, Reporting & Decision Support

• Partner with Finance, Sales, Operations, and other stakeholders to define reporting requirements, KPIs, analytical use cases, and success measures.
• Translate business questions into structured analyses, clearly communicating findings, assumptions, limitations, and recommended actions.
• Proactively identify trends, anomalies, performance gaps, and improvement opportunities in business data, surfacing insights that may not be immediately apparent through standard reporting.
• Support planning, forecasting, variance analysis, executive reporting, and other decision-support activities through high-quality data analysis.
• Use business knowledge and technical understanding to connect reporting needs with the underlying data sources, logic, and transformation requirements.
• Create dashboards, reports, datasets, and modeling tools that allow cross-functional teams to evaluate what-if scenarios and understand the impact of changes in sales, volume, price, margin, cost, inventory, yield, waste, throughput, service, and forecast accuracy.
• Help develop and apply analytics standards, best practices, and reusable assets that support scalable reporting, modeling, and decision-making across functions.
• Promote consistency in data definitions, business logic, documentation, and dashboarding practices to improve trust and maintainability of analytical outputs.

Automation & Data Quality

• Build reusable data assets, automated workflows, and semantic layers that standardize data access and reduce manual reporting effort.
• Implement data quality checks, reconciliation routines, documentation, and governance practices for critical datasets, dashboards, and automated workflows.
• Troubleshoot data issues, perform root-cause analysis, and partner with data engineering, IT, and business teams to resolve source-system, transformation, and reporting discrepancies.

You are best suited for the role if you...

• Bachelor's degree in Finance, Economics, Business Analytics, Data Science, Information Systems, Computer Science, Engineering, Mathematics, Statistics, or a related quantitative or technical field.
• 5+ years of experience in data analytics, business intelligence, analytics engineering, data engineering, financial analytics, commercial analytics, or a related data-focused role.
• Advanced working knowledge of SQL, data analysis, data modeling, KPI development, reporting models, dashboard development, and data visualization tools such as Power BI or similar platforms.
• Experience delivering dashboards, automated reporting workflows, curated datasets, semantic models, SQL transformations, or reusable data assets used by business stakeholders.
• Ability to bridge business and technical requirements, document assumptions and data logic, manage priorities, and communicate clearly with business users, leadership, and technical partners.

Preferred Qualifications & Technical Skills

• Hands-on experience with Power BI, SAP data, SQL, Microsoft Fabric, cloud analytics platforms, data warehouses, lakehouses, or pipeline orchestration tools preferred.
• Experience supporting Finance, FP&A, Sales, Supply Chain, Operations, or Manufacturing analytics.
• Exposure to Python, ETL/ELT concepts, forecasting, statistical analysis, machine learning, or AI-enabled productivity tools preferred.
• Utilize Microsoft Copilot and other AI-enabled tools to identify workflow efficiencies, automate repetitive analysis or reporting tasks, and improve productivity across data preparation, documentation, and business insight generation.
• Familiarity with data quality practices, governed reporting datasets, semantic models, reusable data assets, and practical data engineering standards.

Key Competencies

• Hybrid analytical and technical problem solving with strong business acumen
• Advanced SQL, reporting, dashboarding, data modeling, and data visualization capability
• Ability to translate business needs into analysis, reporting lo