Analytics & BI Application Specialist

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).