Lead Data Engineer-SCM Integration & AWS Databricks
Core
Design, build, and operate scalable data pipelines and analytics solutions to enable end-to-end supply chain visibility and customer collaboration.
Role type
Senior hands-on IC data engineer (supply chain analytics)
Builds
Production-grade ELT/ETL workflows, data products, and cloud-native data solutions for supply chain functions.
Domain
Supply chain analytics, life sciences/manufacturing, enterprise cloud data platforms
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Databricks, Apache Spark, Python, SQL, Apache Airflow, AWS data platforms (S3, Glue, Lambda, EMR, Redshift), data modeling, data integration, data quality, pipeline monitoring, medallion architecture, Delta Lake
Preferred skills
Supply chain domain knowledge (demand planning, procurement, logistics), digital supply chain transformation, CI/CD, DataOps, automated testing, cross-functional global team collaboration
Technologies
Databricks, Apache Spark, Python, SQL, Apache Airflow, AWS (S3, Glue, Lambda, EMR, Redshift), Delta Lake
Responsibilities
Design and maintain scalable data pipelines; Develop ELT/ETL workflows; Connect customer collaboration data with supply chain functions; Orchestrate and monitor data pipelines; Engineer cloud-native data solutions; Apply lakehouse and medallion architecture patterns; Optimize Spark jobs for performance and cost; Embed data quality checks and governance; Partner with business stakeholders and analytics teams; Translate business requirements into technical designs; Support testing, deployment, and production support; Mentor junior data engineers.
Seniority
Senior, hands-on IC
