GCP Analytical Engineer - S

Key Responsibilities

• Design, develop, and maintain analytics-ready data models and datasets on GCP.
• Transform raw enterprise data into clean, scalable, and reusable business data layers.
• Build and optimize ELT pipelines using modern cloud-based technologies.
• Partner with business stakeholders, data analysts, data engineers, and data scientists to define reporting and analytics requirements.
• Develop dimensional models, data marts, and semantic layers to support enterprise reporting.
• Ensure data quality, governance, consistency, and business rule standardization.
• Improve performance and cost efficiency of analytics workloads within BigQuery.
• Support BI and visualization tools by providing curated datasets and metrics.
• Create and maintain data dictionaries, metadata repositories, and business glossaries.
• Enable self-service analytics capabilities across business functions.
• Collaborate with engineering teams to improve data architecture and scalability.

Key Technical Responsibilities

Google Cloud Platform (GCP)

• BigQuery
• Cloud Storage
• Dataflow
• Dataplex
• Cloud Composer
• Pub/Sub
• BigLake
• Vertex AI (Exposure Preferred)

Analytics Engineering

• Data Modeling
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• Data Mart Development
• Semantic Layer Design
• Metrics Definition Framework
• Data Transformation
• Data Validation & Reconciliation

Business Intelligence & Reporting

• Looker
• Looker Studio
• Tableau
• Power BI
• Business Reporting Frameworks
• KPI Development
• Executive Dashboards
• Self-Service Analytics