Lead Data Engineer-SCM Integration & AWS Databricks

Lead Data Engineer-SCM Integration & AWS Databricks — Lead Data Engineer – Bengaluru Build end‑to‑end data pipelines that power Digital Customer Collaboration and supply‑chain analytics for a global leader in scientific solutions. You’ll turn raw supply‑chain data into reliable, cloud‑native data products that improve visibility for customers and internal teams. What You’ll Do Design and maintain scalable ELT/ETL pipelines on Databricks and Apache Spark. Orchestrate workflow schedules with Apache Airflow and monitor pipeline health. Implement lakehouse and Delta Lake patterns to create reusable data assets. Engineer cloud‑native solutions using AWS S3, Glue, Lambda, EMR, and Redshift. Optimize Spark jobs for performance, cost efficiency, and fault tolerance. Embed data‑quality checks, governance controls, and automated testing. Travel to stakeholder sites up to 25% of the time. What You Need 6–10 years of data‑engineering experience in enterprise environments. Strong hands‑on expertise with Databricks, Apache Spark, Python, and SQL. Proven ability to build production‑grade ELT/ETL pipelines. Experience with Apache Airflow (or similar) for workflow orchestration. Deep knowledge of AWS data services: S3, Glue, Lambda, EMR, Redshift. Solid understanding of data modeling, integration, and pipeline monitoring. Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. Good to Have Exposure to supply‑chain domains such as demand planning, procurement, or logistics. Experience with Delta Lake, medallion architecture, and DataOps CI/CD practices. Background in regulated life‑sciences or global manufacturing environments. The Opportunity Join a fast‑growing Supply Chain Analytics team where you’ll partner directly with business stakeholders and senior