Back
Senior, highly specialized Principal data engineering role with strict 15-year requirement reduces candidate density.
Requires deep data engineering, cloud and regulated-industry experience, making skills less transferable across industries.
Explicit 15-year minimum plus mandated technical leadership and specialised platform skills makes shortlisting very strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead and manage a high-performing data engineering team delivering robust, scalable data solutions for Commercial Effectiveness Value Pool to support analytics and AI use cases.
Own full data engineering lifecycle in assigned domain, ensuring data solutions embed quality, security, governance, and align with enterprise standards.
Drive platform automation, compute/storage optimization, and enforce engineering best practices and technical standards across the organization.
Minimum 15 years experience as full-time data or software engineer.
Bachelor’s degree in Engineering, Mathematics, Statistics, or Computer Science.
Proven experience building data solutions for Commercial Effectiveness or related Value Pools and associated data domains.
Work Experience Required: Minimum 15 years as full-time data engineer or software engineer.
Experienced technical leader combining hands-on engineering expertise with management and delivery accountability in enterprise-scale data environments.
Strong domain understanding of Commercial Effectiveness data and analytics needs, with proven ability to translate business requirements into production-ready data assets.
Expertise in scalable data engineering including DevOps automation, cloud platforms (preferably Azure/GCP), Big Data (Spark, Databricks), streaming architectures (Kafka, Event Hubs), and adherence to enterprise data governance.