Manufacturing Analytics Lead

Tree Island Steel•Richmond, BC

12d•Onsite

About The Position

The Manufacturing Analytics Lead serves as the primary architect for the facility’s digital and data infrastructure. This role is responsible for the end-to-end integration of industrial machine and shop floor data, with enterprise-level business systems. The successful candidate will operate at the intersection of IT and Operational Technology, utilizing IBM DataStage for data engineering, QAD ERP for operational data management, and the Cognos/Power BI suites for advanced data visualization and business intelligence.

Requirements

Bachelor’s degree in Computer Science, Industrial Engineering, Data Science, or a related technical field.
Minimum of 5 years of experience with IBM DataStage, Power BI, and Cognos BI.
Demonstrated experience working with an ERP within a manufacturing environment.
Ability to work effectively within a high-speed manufacturing environment, adhering to all safety protocols and PPE requirements.
Strong analytical, problem‑solving, and prioritization skills.
Ability to work collaboratively in a fast‑paced, dynamic environment.
Excellent verbal and written communication skills.

Responsibilities

Act as the primary custodian of manufacturing data, ensuring its accuracy, availability, and security across the lifecycle from the devices to the databases.
Define and enforce data ownership protocols to ensure clear accountability for data quality across different production departments.
Establish rigorous data standards to ensure a "Single Version of Truth" across physical production outputs and digital financial records.
Foster high-level collaboration between various departments such as IT, Finance, Production, Business Planning, Customer Service, Maintenance, Shipping and Quality Assurance teams to align technical solutions with operational realities.
Lead cross-functional workshops to bridge the gap between technical data architecture and practical shop-floor applications.
Partner with plant leadership and finance to ensure that analytics initiatives drive measurable business outcomes and ROI.
Serve as the technical lead for QAD ERP data synchronization, ensuring that production metrics, inventory movements, and labor allocations are reflected accurately within the enterprise system.
Design and maintain complex data integration sequences using IBM InfoSphere DataStage to facilitate seamless data flow between various sources and DB2 database.
Take part in installation and configuration of IoT gateways, edge computing devices, and industrial sensors to capture real-time machine-level data.
Facilitate robust communication between machine PLCs and enterprise systems utilizing protocols such as OPC-UA and Modbus.
Actively participate in the design and execution of strategic, forward-looking projects aimed at achieving Industry 4.0 maturity.
Lead the transition from descriptive reporting to prescriptive analytics, leveraging machine learning and AI to optimize production schedules and maintenance cycles.
Provide technical leadership for key projects, including automated data capture, predictive maintenance frameworks, and the pilot-testing of Generative AI tools.
Develop and govern standardized corporate reporting within Cognos BI to support executive decision-making.
Engineer high-velocity, interactive visualizations in Power BI to monitor real-time Key Performance Indicators (KPIs) such as OEE, scrap rates, and throughput.