Analytics & BI Application Specialist
7 days ago
**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.
- 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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