Engineer, Data Platform & Analytics

The Data Platform & Analytics Engineer is the foundation of Carnival Corporation's corporate data capability. This role is responsible for building and maintaining the Snowflake-based data platform, implementing MDM processes to create trusted, governed data assets, and ensuring all data is structured, clean, and AI-ready for consumption by the AI / ML Engineer. The ideal candidate brings deep expertise in cloud data architecture, pipeline engineering, and master data management, with a strong commitment to architectural best practices. This is a highly technical individual contributor role that directly enables the organization's AI and analytics ambitions by ensuring the right data is available, reliable, and fit for purpose. **Essential Functions:** Data Architecture & Snowflake Platform Engineering + Design, build, and maintain a layered Snowflake data architecture covering RAW, MDM, and Curated layers + Apply and enforce architectural best practices across all platform layers including naming conventions, access patterns, and performance optimization + Manage Snowflake environments, warehouses, roles, and resource monitors to ensure platform reliability and cost efficiency + Own the design and documentation of the overall data platform architecture, ensuring scalability as source systems and use cases grow Pipeline Engineering & New Source Integration + Build and maintain ELT/ETL pipelines ingesting data from multiple corporate source systems into Snowflake + Lead onboarding new data sources into the Snowflake data lake, including schema design, transformation logic, and data quality checks + Develop and maintain API-based and file-based integrations as part of the ingestion layer + Own pipeline reliability, scheduling, monitoring, and incident response across all ingestion workflows Master Data Management (MDM) + Implement and maintain the MDM layer using an enterprise MDM platform, producing trusted golden records for key business entities + Design entity models, matching rules, survivorship logic, and deduplication workflows + Manage data lineage from source systems through to the MDM and curated layers + Work with departmental data stewards to validate entity definitions and ensure domain data quality standards are met + Informatica MDM experience is a strong plus; broader enterprise MDM platform experience is required Data Governance & Quality Implementation + Implement data governance standards within the platform using enterprise data governance tooling + Apply classification, tagging, data masking, and access controls consistently across all data layers + Maintain the data catalogue, lineage metadata, and access governance records + Experience with Horizon Data Governance or Informatica Data Governance is a strong plus + Build and maintain dbt models, tests, and documentation to enforce data quality standards across the platform AI Data Readiness + Prepare and maintain curated data layer optimized for AI and ML consumption + Own export patterns that make data available to AI workload Partner with AI/ML Engineers to define data contracts, schema standards, and feature-ready structures + Ensure AI-bound data assets meet quality, completeness and freshness requirements Observability & Platform Operations + Implement observability tooling to monitor pipeline health, data freshness, and anomaly detection at scale. + Own platform cost monitoring and optimization, including warehouse sizing and query performance tuning. + Maintain platform runbooks, architecture documentation, and operational playbooks **Knowledge, Skills & Abilities:** + Scope: The Data Platform & Analytics Engineer operates with significant autonomy over the design and implementation of Carnival Corporation's corporate data platform. This role holds decision-making authority over data architecture, pipeline design, MDM entity modelling, source system integration, and data governance implementation within the platform. Day-to-day work spans ingestion pipeline development, Snowflake layer management, MDM configuration, and ongoing data quality operations. The role works in close partnership with the AI / ML Engineer to ensure curated data layers meet AI workload requirements and collaborates with the Data Governance Lead and departmental data stewards to implement classification, lineage, and access standards. Common challenges include managing complexity across a growing number of source systems, maintaining MDM golden record quality at scale, and ensuring the platform remains performant and cost-efficient as data volumes grow. Candidates who combine strong architecture instincts with a hands-on approach to delivery will thrive in this role. + Problem solving: Demonstrates strong analytical thinking to design, build, and operate a scalable, governed enterprise data platform that supports analytics and AI use cases. Translates complex, multi-source business data requirements into a cohesive Snowflake-based architecture spanning RAW, M