Who we Are:
Lifting Solutions is a high-performing team that engineers, manufactures, distributes, sells, and services artificial lift products that outperform the market. Since our inception in Canada in 2014, we have expanded from 14 colleagues to over 300 across 28 locations in three countries and distributors in seven additional countries. We are proud to operate two state-of-the-art manufacturing facilities, one in Canada and one in Oman, where we leverage the latest technology to deliver high-performance products to clients worldwide.
Are you interested in applying data, analytics, and process improvement skills to solve real operational challenges in a manufacturing and service environment?
We are seeking a Data & Business Analyst to support initiatives focused on operational efficiency, manufacturing performance, planning, and business process improvement.
The organization maintains significant operational, manufacturing, quality, and financial data across enterprise systems, reporting tools, internally developed applications, and production environments. Opportunities exist to improve how this data is accessed, connected, and used to support decision-making.
In this role, you will work with stakeholders across operations, manufacturing, finance, supply chain, and technology teams to identify practical opportunities for improving data quality, process efficiency, and business insight. Projects will focus on solving business challenges using data and systems.
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Assist with improving access to operational and financial data currently available in enterprise reporting platforms
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Support creation of business-friendly datasets, reports, and analytical tools
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Help document relationships between key business data sources
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Work with business users to better understand data requirements and reporting needs
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Analyze product, service, and asset-related data to identify patterns, trends, and opportunities for improvement
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Support initiatives aimed at improving data quality and integrity across operational systems
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Assist with developing reports and monitoring tools that help identify data inconsistencies and business process issues
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Work with teams to improve the reliability of client-facing and operational information
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Analyze production, inspection, and quality-related datasets to identify relationships between manufacturing processes and product outcomes
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Support investigations into manufacturing performance, quality events, production variability, and process efficiency
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Assist with evaluating correlations between production parameters, inspection results, and product performance
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Contribute to projects focused on reducing manufacturing lead times and improving production planning
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Help identify opportunities to improve planning visibility and decision-making
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Contribute to projects to optimize production scheduling and raw material planning processes
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Support initiatives that improve how operational information is captured and transferred between systems
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Assist with evaluating opportunities to automate manual processes and reduce duplicate data entry
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Help improve the quality and consistency of operational data used by the business
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Participate in projects related to internally developed mobile and cloud-based operational tools
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Work with stakeholders to identify focused business questions that can be answered using existing data
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Develop practical analyses and dashboards that provide actionable insights
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Validate findings with business teams and assist with implementation of recommendations
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Support a culture of data-driven decision-making through incremental and practical improvements
The ideal candidate will have experience or education in one or more of the following areas:
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Business Analytics
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Data Analytics
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Computer Science
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Information Systems
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Data Visualization
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Statistical Analysis
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Process Improvement
Experience with tools such as Excel, SQL, Power BI, Python, R, or similar analytical tools would be considered an asset.
By contributing to this role, the right candidate will gain experience in:
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Operational and business analytics
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Manufacturing and quality data analysis
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Process improvement initiatives
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Planning and forecasting support
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Data quality management
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Enterprise and operational systems
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Cross-functional stakeholder engagement
Projects will focus on delivering practical improvements that support operational efficiency, manufacturing performance, planning accuracy, data quality, and business insight.
