Enterprise Data Analyst

Pure Flavor® Farms•Leamington, ON

20d•$72,000 - $85,000

About The Position

The Enterprise Data Analyst designs, builds, and supports enterprise data solutions and system integrations that enable reliable reporting, automation, AI-enabled business outcomes, and data-driven decision making. This role develops and maintains data pipelines, integrates business applications via APIs/EDI/flat files, improves data quality and governance, and partners with stakeholders to deliver analytics and AI-enable initiatives. The analyst works closely with IT, vendors, and business teams to lead technical delivery, troubleshoot data and integration issues, and continuously improve the organization's data capabilities.

Requirements

Completion of secondary school (high school diploma or equivalent) is required.
Minimum of three(3) years of experience in data, analytics, integration, or related IT roles.
Ability to self-manage work and lead technical delivery from initiation through deployment and support.
Strong SQL skills and experience with data modelling and transforming data for analytics and reporting.
Experience developing and administering Power BI semantic models and reports/dashboards (including Power Query and DAX), plus workspace governance (permissions, publishing standards, refresh schedules, and gateways).
Experience developing data pipelines and automation using tools/languages such as SQL, PowerShell, Python, and/or JavaScript.
Experience with integration methods such as REST/SOAP APIs, EDI, and flat-file exchanges, including incident troubleshooting and coordination with vendors.
Proficiency in Microsoft Office (Excel, Word, PowerPoint) and the ability to produce clear technical documentation.
Ability to work effectively with technical and non-technical stakeholders and communicate status, risks, and options clearly.
Ability to maintain strict confidentiality of sensitive information.

Nice To Haves

Experience with modern data platforms and BI tools(e.g. Power BI, Microsoft Fabric, Azure data services), including semantic modelling, report performance tuning, and BI administration/governance practices preferred.
Experience with the Microsoft Power Platform (Power Apps, Power Automate) and integrating workflows with data sources preferred.
Exposure to AI/ML concepts and experience working within the Software Development Lifecycle (SDLC), including testing and release management preferred.

Responsibilities

Develop, maintain, and optimize enterprise data models, pipelines, and datasets to support reporting, analytics, and operational needs.
Monitor data pipeline health and performance; troubleshoot failures and implement preventative improvements.
Partner with stakeholders to translate business requirements into scalable data solutions and cleats, reliable metrics.
Identify, prototype, and deliver AI-enabled use cases (e.g. document extraction, forecasting, anomaly detection, and copilots) in collaboration with business stakeholders.
Establish repeatable patterns for safe AI adoption, including data readiness, evaluation, and operational hand-off.
Design, build, and support integrations between business applications using API’s, EDI, flat-file exchanges.
Implement monitoring, alerting, and operational procedures for integrations; triage incidents and coordinate fixes with internal teams and vendors.
Design, develop, publish, and maintain Power BI reports and dashboards, including data modeling, DAX measures, and performance optimization.
Administer and govern Power BI workspaces (structure, access/permissions, deployment practices, refresh schedules, gateways, and publishing standards) to ensure secure, reliable, and scalable reporting.
Gather reporting requirements, define KPIs, and support business users through dashboard enhancements, data validation, and guidance on self-service reporting.
Lead technical workstreams for data and integration projects, including scope definition, effort estimation, timelines, and risk/issue management.
Coordinate with cross‑functional teams and vendors to deliver solutions; provide clear status updates and ensure production readiness.
Implement data quality validation, reconciliation, and exception handling to improve trust in enterprise reporting and downstream processes.
Maintain data definitions and access standards in partnership with stakeholders; support appropriate security, privacy, and retention requirements.
Create and maintain documentation for data products, integrations, runbooks, and troubleshooting procedure; share knowledge with IT and business teams.
Provide operational support for enterprise data and integration, including participation in and on-call rotation as required.
Other core expectations as defined by the company.