Project Manager – Digital Manufacturing

Dalisoft Technologies Inc.; India; Vor Ort; Vollzeit

Jobbeschreibung

Join our team of engineers, innovators, and digital transformation experts. Explore opportunities to shape the future of Industry 4.0 with Dalisoft.

Assist senior engineers in building and maintaining robust data pipelines for ETL/ELT processes. Gain hands-on experience working with large industrial datasets from manufacturing sources like sensors, machines, and ERP systems. Support real-time analytics initiatives by cleaning, transforming, and validating data. Expected to learn and contribute to projects involving time-series data, Python-based data workflows, and SQL-based query optimization. Exposure to cloud services such as AWS/GCP and tools like Airflow is a plus.

Design, build, and optimize large-scale, production-grade data architectures that support real-time manufacturing analytics. Lead the development of data ingestion frameworks using Apache Kafka, Spark Streaming, or Flink. Implement data governance, quality checks, and monitoring in industrial data environments. Mentor junior engineers and work closely with IT/OT teams to integrate shop-floor and enterprise data. Experience with time-series databases, CI/CD for data pipelines, and data modeling for IoT telemetry is highly preferred.

Deploy smart manufacturing solutions involving IoT devices, industrial sensors, PLCs, and SCADA systems. Integrate data across OPC UA, MQTT, Modbus, and other industrial communication protocols. Contribute to edge computing systems using gateways and deploy digital twin models of machines or processes. Ideal candidates will be comfortable working with industrial control systems, developing logic in ladder or structured text, and collaborating with automation teams on factory digitization.

Oversee the planning and execution of digital transformation initiatives in manufacturing environments. Manage cross-functional teams, vendor interactions, and Agile workflows for successful delivery. Responsibilities include risk identification, sprint planning, stakeholder reporting, and change management. Must be familiar with Industry 4.0 technologies, including MES, SCADA, and cloud platforms. PMP, Prince2, or Agile certification and experience with Jira/Confluence is highly desirable.

Work with clients to gather business requirements and translate them into functional specifications for ERP systems. Design and map manufacturing processes across production, procurement, inventory, sales, and finance modules. Conduct GAP analysis, UAT sessions, and end-user training. Candidates should have experience with one or more ERP systems (SAP S/4HANA, Oracle Fusion, Odoo) and knowledge of production planning, BOM, routings, and MRP concepts.

Build, deploy, and maintain machine learning models for applications in predictive maintenance, process optimization, and quality anomaly detection. Use libraries such as scikit-learn, TensorFlow, or PyTorch to train and validate models on industrial datasets. Work closely with data engineering and domain teams to define model features and deployment pipelines. Experience in edge AI deployment, time-series modeling, and familiarity with industrial protocols or MES systems is a plus.

Design and develop real-time dashboards, operational KPIs, and data visualizations for manufacturing clients. Create intuitive and responsive user interfaces using tools like Power BI, Tableau, or Grafana. Proficiency in SQL, DAX, and performance tuning of analytical queries is essential. Ideal candidate understands time-series analysis, production cycle efficiency metrics (OEE, TEEP), and has worked with industrial databases or APIs from MES/SCADA systems.

Use statistical techniques, clustering, forecasting, and classification algorithms to generate actionable insights from manufacturing data. Analyze MES, quality, and operational datasets to identify patterns and optimization opportunities. Skilled in Python, pandas, matplotlib/seaborn, and model interpretability libraries (e.g., SHAP, LIME). Knowledge of manufacturing KPIs, downtime root-cause analysis, and working with OT systems will be a strong asset.

Lead strategic marketing initiatives tailored to the digital manufacturing sector. Develop product messaging, white papers, customer case studies, sales presentations, and content for web and social campaigns. Should possess a solid understanding of industrial automation, Industry 4.0, and smart manufacturing. Experience working with B2B clients, marketing automation tools, and ability to collaborate with tech teams for product positioning is essential.

Join our structured internship program where interns will participate in live client or R&D projects in smart factory systems, data pipelines, machine learning, and industrial cybersecurity. Get mentored by experienced engineers and contribute to components of digital twins, predictive maintenance models, and MES interfaces. Successful candidates may receive full-time job offers based on performance and technical contributions.