Terra Aqua Environmental Consultancy Limited is a Metal Recycling Plant a prominent player in the recycling industry. Specializing in the conversion of aluminum scraps and Used Beverage Cans (UBC) into high-quality aluminum ingots, our plant initially boasted a production capacity of 1200MT per month. Driven by a commitment to innovation and sustainability, we expanded our operations with a state-of-the-art facility with an installed capacity of 8,600MT of aluminum alloy ingots per month. This expansion underscores our dedication to addressing both environmental challenges and market demands.
Job Role
- The Data Analyst will play a critical role in supporting Terra Aqua Environmental Consultancy Limited’s Metal Recycling Plant operations by collecting, analyzing, and interpreting production, maintenance, financial, and supply chain data.
- The role is responsible for transforming raw operational data into actionable insights that drive efficiency, sustainability, compliance, and profitability.
- The analyst will work closely with Operations, Maintenance, ESG, Finance, and Senior Management to design reporting systems, build dashboards, and provide decision-support analyses.
- This is an experienced-level position requiring a strong background in industrial/manufacturing data analytics, proven ability to design and maintain databases/dashboards, and the ability to work with large, complex datasets.
Key Responsibilities
Data Management & Reporting:
- Design, implement, and maintain databases for production, equipment, maintenance, and other operational data.
- Ensure accuracy, completeness, and timeliness of daily data capture (production logs, equipment performance, maintenance logs, energy use).
- Develop and maintain real-time dashboards and reports in tools such as Power BI, Tableau, or Airtable.
- Establish and enforce data governance standards across departments.
Production & Process Analytics:
- Analyze furnace-level data (inputs, hot ingots, recovery %, capacity utilization) to identify efficiency trends, bottlenecks, and anomalies.
- Monitor scrap feedstock quality, yield, and recovery efficiency to recommend process improvements.
- Provide variance analysis between planned vs actual production and recommend corrective actions.
Maintenance & Asset Analytics:
- Track downtime, repair costs, spare parts usage, and preventive maintenance schedules.
- Support predictive maintenance by analyzing breakdown history and usage trends.
- Provide cost-per-equipment and lifecycle insights to support replacement vs repair decisions.
Financial & Business Analytics:
- Collaborate with Finance to monitor unit cost of production, repair costs, and margins.
- Build cost models for scrap procurement, energy usage, and logistics.
- Provide management with profitability and efficiency dashboards.
Stakeholder Communication & Decision Support:
- Present insights in clear, business-friendly reports and presentations for management and board meetings.
- Support regulators and investors with accurate, auditable data.
- Train operations staff on data capture tools and dashboard usage.
Key Performance Indicators (KPIs) for the Role
- Accuracy and completeness of daily production and maintenance data.
- Number and quality of dashboards/reports automated.
- Reduction in downtime through predictive analytics insights.
- Improvement in production yield/recovery through data-driven recommendations.
- Management satisfaction with data quality and insights.
Requirements
Educational Qualification
- Bachelor’s Degree in Data Analytics, Statistics, Computer Science, Engineering, Industrial/Production Management, or related field.
- Master’s Degree in Data Science, Business Analytics, or related field is an advantage.
Experience:
- Minimum 4–6 years of proven experience as a Data Analyst in manufacturing, heavy industry, recycling, or related environment.
- Demonstrated track record in designing dashboards, building data pipelines, and conducting in- depth operational analytics.
- Experience with production process data preferred.
Technical Skills:
- Strong proficiency in data visualization & reporting tools: Power BI, Tableau, or equivalent.
- Advanced Excel skills (pivot tables, power query, VBA).
- Proficiency with databases and SQL for managing large datasets.
- Experience with Python or R for advanced analytics and automation will be an advantage.
- Familiarity with ERP systems and integration of operational data.
- Knowledge of predictive analytics for maintenance (machine learning preferred but not required).
Industry Knowledge:
- Understanding of industrial production processes, furnaces, recycling, or heavy equipment operations will be an advantage.
- Familiarity with supply chain and logistics analytics in a manufacturing context.
Soft Skills:
- Strong analytical and problem-solving skills.
- Ability to translate complex data into actionable insights for non-technical stakeholders.
- Excellent written and verbal communication skills.
- High attention to detail and data accuracy.
- Ability to work cross-functionally with operations, maintenance, finance, and ESG teams.
Method of Application
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