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Popular data-manager title and likely metro hiring increase competition, but senior 10+ years requirement reduces density.
Core data engineering skills are transferable, but SAP/Salesforce and ecommerce integrations increase domain specificity.
Multiple explicit requirements: 10+ years, managerial experience, GCP/BigQuery, Airflow, Terraform, Looker.
Define and own the enterprise-wide Data & Analytics architecture and project roadmap including ingestion, transformation, storage, governance, reporting, and AI/ML/Data Science capabilities.
Architect and deliver scalable, secure, and optimized data infrastructure on GCP, incorporating BigQuery, Cloud Functions, orchestration, and automation frameworks.
Lead integration of data platforms with SAP, Salesforce Marketing Cloud, Salesforce Commerce Cloud, and build semantic layers and self-service analytics foundations.
3+ years experience as Data Solution Architect or Data Engineering Manager with leadership responsibilities.
10+ years experience in Data Engineering and modeling of DataMarts or business semantic data layers, BI, Analytics, AI/ML in large-scale Lakehouse architecture.
Strong technical skills with data pipeline tools (Apache Airflow, Cloud Composer, GCP Dataflow, Dataform), cloud platform design specifically GCP, Terraform for IaC, SQL, and Python.
Experience integrating data platforms with SAP, Salesforce Marketing Cloud, and e-commerce platforms.
Senior-level professional with deep expertise in designing and managing enterprise-scale cloud data platforms on GCP.
Experienced in leading teams and complex data architecture projects across multiple business systems and domains.
Strong operational focus on building scalable, governed, and automation-ready data and analytics ecosystems integrated with enterprise software (SAP, Salesforce).