-

Start Date: ASAP
Work Model: Hybrid 
Location: Downtown Toronto (outside Union Station – TTC & GO accessible)
Dress Code: Business Casual 
A Great Place to Work

Who We Are

Founded in 1993, Kinross is a Canadian-based senior gold mining company with operations and projects in the United States, Brazil, Mauritania, Chile and Canada. Our focus on delivering value is based on our four core values of Putting People First, Outstanding Corporate Citizenship, High Performance Culture, and Rigorous Financial Discipline.

Mining responsibly is a priority for Kinross, and we foster a culture that makes responsible mining and operational success inseparable. Our values-based approach ensures that sustainability and our environmental, social and governance commitments are a core part of our strategy and plans for future growth. In line with our values, we also aim to build meaningful partnerships with all of our stakeholders, including communities, shareholders, employees, governments and suppliers.

Kinross maintains listings on the Toronto Stock Exchange (symbol: K) and the New York Stock Exchange (symbol: KGC).

Job Summary

Reporting to the Sr. Director of Data Management and Analytics, the Manager of Reporting, Analytics is responsible for leading the design, implementation, and continuous evolution of Kinross’s reporting, analytics, and enterprise data modelling capabilities. This role plays a central part in the team’s mission to deliver trusted, timely, and business-ready data products across the organization.

The Manager leads a team of analysts, overseeing a broad portfolio that spans self-service BI, certified reporting, day to day analytics, semantic layer development, and the governance of data models that underpin Kinross’s Cloud Data Ecosystem — built on Azure Data Factory, Databricks, and Power BI. Beyond technical delivery, this role acts as a strategic bridge between IT and the business, translating evolving stakeholder needs into scalable analytical solutions and cultivating a data-driven culture across the enterprise.

Job Responsibilities

Reporting & Analytics (35%)

• Lead the evolution of Kinross’s analytics maturity model: expanding beyond descriptive and diagnostic analytics (what happened, why it happened) to enable predictive analytics (what will happen) and prescriptive analytics (what should be done), in close collaboration with the Data Engineering function.
• Define and enforce a certified reporting standard, establishing governance over report creation, publication, and lifecycle management to ensure the organization has a single source of truth for operational and strategic metrics.
• Oversee the design, development, and maintenance of dashboards, reports, and data visualization solutions in Power BI, ensuring accuracy, completeness, and timeliness across all reporting deliverables.
• Implement and manage the Kinross Analytics Framework, defining analytics personas and content strategies tailored to consumers, explorers, and innovators — and delivering specialized enablement and training programs within and outside of IT.
• Promote a self-service analytics culture by enabling business users to independently explore data through governed, user-friendly tools and curated semantic models.
• Act as a strategic liaison between the analytics team and business units, translating data needs into actionable insights and recommendations that support operational and corporate objectives.
• Manage escalated level 2–3 support of Reporting and Analytics applications, ensuring service continuity and a high standard of user experience.
• Stay current with industry trends and emerging technologies in analytics, BI, and AI-assisted reporting, continuously identifying opportunities to enhance the team’s capabilities.

-

Data Modelling (35%)

• Establish and lead the Data Modelling capability within the Reporting & Analytics team, defining standards, methodologies, and best practices for semantic and dimensional modelling across the Kinross Cloud Data Ecosystem.
• Own the design and governance of the enterprise semantic layer in Power BI (including datasets, dataflows, and Direct Lake models), ensuring business definitions are standardized, certified, and reusable across reports and analytical use cases.
• Drive the implementation of dimensional modelling patterns (star schemas, snowflake schemas, slowly changing dimensions) within the Kinross Databricks Lakehouse, enabling scalable data products that serve both BI and advanced analytics consumers.
• Collaborate with Data Engineers to align data pipeline outputs with downstream modelling requirements, ensuring fit-for-purpose data structures are available in the Gold layer of the data lakehouse.
• Define and maintain a business glossary and data dictionary, ensuring that metric definitions, KPI logic, and entity relationships are documented, governed, and accessible to both technical and business audiences.
• Evaluate and introduce modern modelling frameworks and tooling (e.g., dbt, Databricks Unity Catalog) to improve model development velocity, testability, and lineage visibility.

Data Governance & Information Architecture (10%)

• Lead initiatives to improve data accessibility, usability, and discoverability for business users across Kinross operations and corporate functions.
• Contribute to the Data Governance program by defining and enforcing data quality standards, ownership policies, and access controls for analytics and reporting domains.
• Oversee the cataloguing of existing data sources and the documentation of data lineage from source systems through the lakehouse layers (Bronze, Silver, Gold) to end-user reports and data marts.
• Champion data literacy across the organization through structured training programs, community of practice initiatives, and the promotion of consistent data standards and definitions.
• Collaborate with the Data Management and CyberSecurity teams to ensure compliance with data privacy, security, and governance requirements across all analytics deliverables.

Application Development & Integration Practices (10%)

• Assess integration and analytics requirements by producing business requirements for data, identifying data sources, and delivering data specifications including mapping, transformation rules, and quality expectations.
• Conduct initial data exploration and profiling activities (binning, pivoting, summarizing, correlation analysis) to validate data fitness for reporting and modelling purposes.
• Collaborate with Data Engineers and the Data Science team to ensure analytics pipelines are aligned with modelling and reporting requirements, and that SDLC processes are consistently followed.

Leadership & Team Management (10%)

• Lead, mentor, and develop a high-performing team of analytics professionals, fostering a culture of curiosity, quality, and continuous improvement.
• Set clear performance goals, provide regular feedback, and create development opportunities aligned with both individual growth and team capability needs.
• Develop project plans, allocate resources, and monitor progress against milestones, proactively managing risks and communicating status to senior stakeholders.
• Evaluate and recommend new tools, technologies, and methodologies to enhance the team’s analytics and modelling capabilities.
• Contribute to the recruitment and onboarding of new team members, ensuring role clarity and a strong start for new hires.

Qualifications and Experience

• Bachelor’s degree in IT, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field. A Master’s degree is considered an asset.
• Minimum 6+ years of progressive experience in data analytics, business intelligence, or a related field, including at least 2 years in a people management or team lead role.
• Demonstrated experience designing and governing data models (dimensional or semantic) in a modern cloud analytics environment.
• Proven ability to lead cross-functional analytics initiatives, manage multiple projects simultaneously, and deliver results in a fast-paced environment.
• Excellent problem-solving skills with strong attention to data quality, accuracy, and governance.
• Strong verbal and written communication skills with the ability to convey complex data concepts to non-technical stakeholders including senior management.
• Experience in the mining, resources, or industrial sectors is considered an asset.
• Fluency in Spanish, Portuguese, French, or Arabic is considered an asset.

Required Technical Knowledge

Core (Mandatory)

• Advanced proficiency in Power BI, including report and dashboard development, dataset design, DAX authoring, row-level security, and deployment pipeline management.
• Deep understanding of dimensional modelling concepts: star schemas, snowflake schemas, slowly changing dimensions, and fact/dimension table design.
• Strong SQL skills with experience writing and optimizing complex queries against relational and analytical databases.
• Solid knowledge of data lifecycle management, data warehousing concepts, and the lakehouse architecture (Bronze / Silver / Gold layers).
• Familiarity with Azure Databricks and Azure Data Factory as core components of a cloud data ecosystem, including an understanding of how data flows through the platform to serve analytics consumers.
• Experience with data governance practices, including data cataloguing, lineage documentation, and the management of business glossaries and certified datasets.

Nice to Have

• Hands-on experience with dbt (data build tool) or similar transformation frameworks for model development, testing, and documentation in a lakehouse environment.
• Experience with Databricks Unity Catalog for data discovery, lineage tracking, and access governance.
• Familiarity with Power BI Fabric (Microsoft Fabric), including Direct Lake connectivity, OneLake integration, and semantic model management.
• Knowledge of Python or PySpark for data exploration, ad hoc analysis, or automation of reporting workflows.
• Experience with ERP systems (e.g., Oracle JD Edwards) and operational data sources common in mining environments (e.g., Fleet Management Systems, Process Historians).
• Understanding of MLOps or AI/ML model integration within BI and analytics platforms.
• Technologies:
• Mandatory: Power BI, Azure Databricks, Azure Data Factory, SQL Server, Git / Azure DevOps
• Recommended: Microsoft Fabric, dbt, Databricks Unity Catalog, Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Oracle JD Edwards, Python.

Required Behavioral Competencies

• Communication – demonstrated strength in communicating with internal and external customers, vendors, project teams, and senior management. Strong ability to build relationships, work collaboratively, and resolve problems with people at all levels of the organization.
• Leadership – as a solutions-oriented leader, fosters a culture of creativity, innovation, accountability, and proactivity. Leads by example and invests actively in the growth of team members.
• Strategic Thinking – ability to connect day-to-day analytics delivery to longer-term business strategy, identifying opportunities to expand the team’s impact and influence across the organization.
• Flexibility – the ability to adapt to changing conditions and priorities, to use feedback from the team and the broader organization to change course if deemed necessary. Willingness to learn continuously across both business and technology domains.
• Innovation – willingness to embrace new, improved, and unconventional ways to address business and technical challenges, and to champion the adoption of modern analytics and modelling practices.
• Accountability – takes ownership of team output and outcomes. Willing to acknowledge successes, learn openly from setbacks, and create an environment where the team feels safe to do the same.
• Travel – willingness to travel up to 15%.

Compensation and Total Rewards

The base salary range for this role is $125,000 to $150,000 CAD plus a target Short-Term Incentive bonus of 25% and group benefit coverage.

The hiring range reflects our targeted compensation framework for the role. The actual offer will be determined through a comprehensive evaluation of each candidate’s experience, capabilities, and potential impact, along with consideration of internal equity, team structure, and benchmark market data for similar positions.

In addition to base salary, Kinross offers a comprehensive total rewards package designed to support employee well-being, performance, and long-term development.

Use of AI in Our Hiring Process

We use AI-enabled tools to help sort and review applications based on job-related criteria. All hiring decisions, including who moves forward in the process, are made by a human.

Existing Vacancy

This job posting is for an existing vacancy.