Greenscape Eco Management is a pioneering Indian urban-mining company, founded in 2007, that transforms end-of-life electronics and electrical goods into valuable secondary materials. Rather than viewing disposed TVs, refrigerators, washing machines, air conditioners, and other electronic waste as mere refuse, Greenscape treats them as urban minessources of precious and base metals such as gold, copper, aluminium, and rare earths.

Through advanced recovery processes and a robust circular-economy framework, Greenscape has recycled tens of thousands of metric tons of electronic waste and extracted over 40 different metals and minerals.

By doing so, the company reduces environmental footprint, curbs demand on virgin raw-material mining, and contributes to sustainable resource management, aligning with broader climate, resource conservation, and social goals.

Job Summary:

- The Associate Director - Product Engineering (Digital Manufacturing Systems) is responsible for architecting, developing, and deploying Greenscape's end-to-end plant digital monitoring ecosystem.

- This role will design and implement integrated software platforms that capture, analyze, and visualize real-time operational data across recycling and manufacturing processes including throughput, yield, downtime, quality, defects, energy consumption, and material traceability.

- The incumbent will lead development of plant-level MES (Manufacturing Execution Systems), IoT integrations, automation dashboards, and ERP implementation & interfaces; creating a unified digital layer connecting shopfloor equipment to enterprise decision systems.

- This is a techno-functional leadership role combining plant engineering knowledge with software systems design.

Key Responsibilities:

1. Digital Plant Architecture Design:

- It is the structured design of hardware + software + data layers that capture plant activity in real time and convert it into operational and financial intelligence.

It answers questions like:

How much scrap came in today (grade-wise)?

What was the metal recovery yield?

Which machine caused downtime?

What defect rate did extrusion produce?

What is cost per MT right now?

Think of the architecture as 5 integrated layers:

L5 - Business Systems Layer (ERP / Finance / Sales)

L4 - Manufacturing Systems Layer (MES / Quality / Traceability)

L3 - Supervisory Layer (SCADA (Supervisor Control & Data Acquisition) / Control Rooms)

L2 - Machine & Automation Layer (PLCs / Sensors / Drives)

L1 - Physical Plant Layer (Shredders / Extruders / Separators)

2. Manufacturing Execution Systems (MES):

- The role must play a leadership role in MES strategy, design, and deployment defining functional requirements, selecting or developing MES platforms, integrating PLC/SCADA data, and ensuring seamless synchronization with ERP for inventory, costing, and production posting.

- The role should oversee MES modules spanning production monitoring, quality management, downtime analytics, maintenance triggers, and yield tracking, while driving user adoption on the shopfloor. Additionally, the position is responsible for ensuring data integrity, designing dashboards for plant and corporate stakeholders, and scaling MES architecture across future Greenscape facilities as part of a standardized Industry 4.0 roadmap.

MES systems should monitor:

- Production throughput (TPD / shift output)

- Line utilization & bottlenecks

- Work-in-progress inventory

- Batch traceability

- Operator productivity

3. Quality & Defect Monitoring System:

- The role is responsible for developing and deploying digital quality and defect monitoring systems that track output performance across all recovered material streams.

- This includes monitoring metal purity, contamination levels, and recovery efficiency; assessing plastics for polymer composition, colour contamination, melt flow characteristics, and odour or filtration performance; and evaluating extrusion outputs for thickness consistency, surface defects, and dimensional stability such as warpage.

- The system should integrate laboratory testing data with shopfloor production data to create unified, real-time quality dashboards that enable defect detection, root cause analysis, and continuous process improvement.

4. Yield & Material Traceability Platform:

- Develop digital yield and material traceability platforms that track scrap intake through to final output recovery, enabling visibility into yield percentages by batch, supplier, and product stream.

- The system should monitor residue generation, process losses, and metal and plastic recovery efficiency while establishing full material genealogy across processing stages. This traceability enables accurate material margin analysis, loss accountability, and data-driven optimization of recovery performance.

5. IoT & Machine Integration:

- Deploy IoT-enabled sensors and machine integrations to enable real-time capture of operational data across shredders, crushers, separators, and extrusion lines.

- The system should monitor critical parameters such as load, speed, temperature, vibration, and energy consumption, creating a live equipment performance layer. This data foundation should further support development of predictive maintenance analytics to anticipate failures, reduce unplanned downtime, and optimize asset reliability and maintenance planning.

6. ERP Integration & Data Synchronization:

- Ensure seamless integration between plant digital systems and the ERP platform to enable automated flow of operational and financial data, including inventory updates, production posting, scrap consumption, finished goods output, and costing inputs.

- This involves designing and deploying APIs or middleware layers that synchronize MES and ERP data in real time, ensuring accuracy, traceability, and alignment between shopfloor activity and enterprise reporting.

7. Downtime & Maintenance Analytics:

- Develop digital systems to capture and analyze equipment reliability data, including breakdown events, planned versus unplanned downtime, MTTR, and MTBF metrics, along with key maintenance cost drivers.

- These platforms should enable root cause analysis through interactive dashboards and deliver reliability analytics that support preventive interventions, cost control, and improved asset uptime.

8. Business Intelligence & Decision Dashboards:

- Develop executive-level digital dashboards that provide real-time visibility into critical plant performance metrics, including throughput versus capacity utilization, yield and recovery rates, quality defect trends, overall equipment effectiveness (OEE), energy consumption, and cost per metric ton processed.

- The system should deliver role-based, customizable views tailored to leadership and operational stakeholders including the Plant Head, CFO, COO, and Quality teams enabling data-driven decision-making across operations, finance, and performance management.

Qualifications Required:

1. Educational Background:

a. B.Tech / M.Tech in Mechanical, Electrical, Industrial, or Automation Engineering

b. MS in Operations / Technology Management (preferred)

2. Professional Experience:

Required:

a. 5-7 years across software engineering + digital systems

b. Experience implementing MES / Industry 4.0 platforms

c. Exposure to plant automation & PLC data integration

Highly Preferred:

a. Recycling / metals / process industry digitalization

b. IoT deployments in heavy industry