Superb opportunity for a leader within the Data Engineering space. In the role youll lead a team of data engineers building scalable, secure, and high-performance data solutions on Databricks and AWS. Youll architect modern data platforms, guide implementation, and ensure best-in-class engineering practices across a global enterprise. Responsibilities Architect and manage Databricks-based Lakehouse platforms (Delta Lake, Spark, MLflow) Integrate with AWS services including S3, Glue, Lambda, and Step Functions Design and optimize scalable ETL/ELT pipelines using Spark (Python/Scala) Automate infrastructure with Terraform or CloudFormation Ensure robust performance tuning of Spark jobs and cluster configurations Implement strong security governance using IAM, VPC, and Unity Catalog Lead a high-performing engineering team through Agile delivery cycles Skills Data Engineering expertise and proven Leadership skills Extensive Databricks experience in production environments Advanced AWS knowledge: S3, Glue, Lambda, VPC, IAM, EMR Strong coding skills in Python (PySpark), Scala, and SQL Expertise in CI/CD pipelines, Git-based workflows, and automated testing Familiarity with data modeling and warehousing (e.g., Redshift, Postgres) Proficient in orchestration and workflow tools (e.g., Airflow, Step Functions) Skills: Data Engineer AWS Azure Databricks Data Architect Business Intelligence Data Manager