Lead Software and Data Engineer

(Job ID: 1678283)

Lead the development of scalable software and data platforms that drive digital transformation across supply chain and enterprise operations.

• Lead the design, development, and implementation of enterprise software applications and data platforms to support business operations and digital transformation initiatives.
• Architect and manage scalable data infrastructure, including data warehouses, data lakes, and modern data platforms to support analytics and operational reporting.
• Develop and maintain data pipelines, ETL/ELT processes, and data integration frameworks to ensure data accuracy, accessibility, and governance.
• Design and implement backend systems, APIs, and microservices to support business-critical applications and platform services.
• Drive the adoption of modern data engineering practices using cloud-based technologies and platforms such as Databricks.
• Collaborate with business stakeholders to gather requirements and translate operational needs into scalable software and data solutions.
• Lead system integration projects involving enterprise applications, ERP systems, warehouse management systems, and third-party platforms.
• Establish best practices for software engineering, data architecture, DevOps, CI/CD, and platform governance.
• Mentor and provide technical leadership to software engineers, data engineers, and cross-functional development teams.
• Monitor system performance, reliability, security, and scalability while continuously improving platform capabilities.
• Support technology roadmap planning and recommend innovative solutions that deliver measurable business value.

• Degree in Computer Science, Information Technology, Data Science, Software Engineering, or a related discipline.
• At least 5 years of experience in software engineering, application development, data engineering, or related fields.
• Proven experience leading technical teams and delivering complex software or data platform projects.
• Strong proficiency in Python for application development, automation, data processing, and system integration.
• Hands-on experience designing and implementing data warehouses, data lakes, and modern data platforms.
• Experience with Databricks, Spark, or similar big data and analytics platforms.
• Strong knowledge of database technologies, including SQL and NoSQL databases.
• Experience developing APIs, backend services, microservices, and enterprise applications.
• Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of containerization technologies, DevOps practices, CI/CD pipelines, and software deployment methodologies.
• Experience integrating enterprise systems such as ERP, WMS, CRM, or other business applications.
• Strong understanding of data governance, data quality, security, and scalability best practices.
• Experience in supply chain, logistics, procurement, manufacturing, or related operational environments is an added advantage.
• Experience in Artificial Intelligence (AI), Machine Learning (ML), predictive analytics, or advanced data modelling is an added advantage.
• Knowledge of time-series forecasting, optimization algorithms, or MLOps practices is an added advantage.
• Strong stakeholder management, communication, and problem-solving skills.