Engineer, Data Platform & Analytics

Carnival Corporation•Miami, FL

1d•Hybrid

About The Position

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.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics or Statistics or a related field.
6+ years of experience in data engineering, data platform engineering, or a closely related technical discipline
Demonstrated experience designing and building production data pipelines and cloud data platforms
Hands-on experience with MDM platforms and enterprise data governance tools
Strong hands-on expertise with Snowflake including architecture design, performance tuning, and platform administration
Proficiency with dbt for data transformation, testing, and documentation
Solid understanding of ELT/ETL pipeline design and orchestration best practices
Experience with AWS S3 and cloud-based data storage and export patterns
Strong MDM experience required: entity modelling, golden record management, deduplication, and survivorship logic
Experience with data governance implementation including classification, lineage, access controls, and data cataloguing
Strong data architecture instincts with a track record of applying and enforcing best practices
Proficiency in SQL and Python for data transformation and pipeline development

Nice To Haves

Informatica MDM experience is a strong plus
Experience with Snowflake Horizon Data Governance or Informatica Data Governance is a strong plus
Familiarity with Snowflake AI tooling and preparing data for ML/AI consumption
Snowflake or dbt certifications

Responsibilities

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
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
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
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
Build and maintain dbt models, tests, and documentation to enforce data quality standards across the platform
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
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

Benefits

Cost-effective medical, dental and vision plans
Employee Assistance Program and other mental health resources
Additional programs include company paid term life insurance and disability coverage
401(k) plan that includes a company match
Employee Stock Purchase plan
Holidays – All full-time and part-time with benefits employees receive days off for 8 company-wide holidays, plus 2 additional floating holidays to be taken at the employee’s discretion.
Vacation Time – All full-time employees at the manager and below level start with 14 days/year; director and above level start with 19 days/year. Part-time with benefits employees receive time off based on the number of hours they work, with a minimum of 84 hours/year. All employees gain additional vacation time with further tenure.
Sick Time – All full-time employees receive 80 hours of sick time each year. Part-time with benefits employees receive time off based on the number of hours they work, with a minimum of 60 hours each year.
Complementary stand-by cruises, employee discounts on confirmed cruises, plus special rates for family and friends
Personal and professional learning and development resources including tuition reimbursement
On-site Fitness center at our Miami campus