Analytics & BI Application Specialist
Delta, British Columbia
Full-time
Responsibilities:
• Act as a liaison between QCA's customers and the development team, ensuring effective communication of business requirements.
• Conduct comprehensive business analysis and gather technical requirements.
• Configure and interface with modern SCADA and industrial historian systems.
• Design, develop, and troubleshoot modern database solutions using cloud-based platforms.
• Implement robust data integration processes for analytics and data transformation.
• Architect and implement scalable, secure cloud-based infrastructures.
• Develop advanced BI solutions and dashboards to support client decision-making.
• Facilitate seamless data flow between industrial control systems and enterprise applications.
• Maintain comprehensive documentation of system architectures, processes, and solutions.
Requirements:
• 2 to 4 years of relevant experience in Analytics, BI, or similar fields.
• Bachelor’s degree in Computer Science, Data Engineering, Industrial Automation, or a related field.
• Proficiency in modern database technologies such as SQL Server, Azure SQL, or PostgreSQL
• Hands-on experience with industrial data historians (e.g., OSIsoft PI, Ignition, Canary Labs).
• Expertise in data integration tools and frameworks (e.g., Apache NiFi, Azure Data Factory, Talend).
• Familiarity with data integration protocols (e.g., OPC UA, MQTT, REST APIs).
• Experience with Business Intelligence and visualization tools (e.g., Power BI, Tableau, Looker).
• Experience with modern version control systems (e.g., Git) and CI/CD practices.
• Analytical thinker with a meticulous eye for detail and a solutions-oriented mindset
• Exceptional interpersonal skills with the ability to convey ideas effectively
• Able to build positive relationship within and across teams
Other qualifications (preferred but not required:
• Knowledge of industrial automation systems (e.g., SCADA, PLC).
• Experience with IIoT platforms and edge computing solutions.
• Familiarity with machine learning frameworks and AI-driven analytics.
• Relevant certifications in cloud technologies or data engineering
• Experience in cloud platforms (Azure, AWS, or Google Cloud).
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