BI Tech Lead – Supply Chain Analytics

About the role

The Lead Data Engineer – Supply Chain Analytics will design, build and maintain scalable data pipelines and curated datasets that provide end‑to‑end visibility across supply‑chain operations. This role blends hands‑on data‑engineering expertise with deep supply‑chain knowledge to support demand planning, inventory, procurement, manufacturing and logistics.

Key responsibilities

• Design, develop and operate robust ETL/ELT pipelines integrating data from ERP, CRM and other supply‑chain systems using cloud platforms such as AWS, Databricks and Redshift.
• Ensure data quality, consistency and reliability through validation, monitoring and performance optimisation.
• Partner with supply‑chain teams to create curated datasets and data models aligned with KPIs like forecast accuracy, inventory planning and service levels.
• Enable timely reporting and analytics, support scenario analysis and performance tracking.
• Prepare data for advanced analytics, including forecasting, optimisation and machine‑learning model deployment.
• Apply data‑quality checks, governance standards and master‑data practices while maintaining documentation, lineage and metadata.
• Collaborate with analytics, IT and data‑science teams to deliver dashboards and BI solutions using Power BI.
• Continuously improve data‑engineering practices and workflows.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Supply Chain or a related field; advanced degree preferred.
• 10‑12+ years of experience in data engineering, business intelligence or analytics, with demonstrated supply‑chain exposure.
• Proven track record delivering data pipelines and analytics solutions at scale.

Required skills

• ETL/ELT pipeline development
• AWS cloud services
• Databricks platform
• Amazon Redshift
• Power BI reporting
• Data validation and monitoring
• Data governance and master‑data management
• Data modeling and metadata documentation