Royal Caribbean Group

3+ years of experience with streaming technologies (Kafka, Pubsub, Kinesis) and log-based architectures and experience writing batch and stream processing jobs (i.e. Apache Beam, Google Cloud DataFlow, Apache Spark, Apache Storm).. 3+ years of experience with ETL/ELT development tools (Azure Data Factory (ADF) preferred).. 3+ years of experience with code version control using tools, such as Git, and experience with Agile tools (Jira or Azure DevOps preferred).. Experienced in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional and new data integration technologies (such as ETL, ELT, data replication, change data captures, message-oriented data movement, API design, stream data integration and data virtualization) Experienced with implementing data quality frameworks.. Expert level knowledge with programming languages including Python, SQL, CLI. Expert level knowledge with relational SQL databases such as Oracle and SQL Server.

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Position Summary The primary focus of this role will be to support the internal organization in implementing and delivering strategies and results. You will be responsible for building, managing, and optimizing reusable enterprise data pipelines effectively and in a timely manner through the development lifecycle to be used by internal consumers, such as data analysts and data scientists. In this role, you will focus on building and enhancing our Revenue Management Automation (RMA) and Revenue 360 data assets. You will use both technical and analytical skills to understand and solve business problems using available resources and current technology stack, while ensuring data governance and data security compliance. You will also mentor junior engineers in finding optimal and efficient solutions for designing, preparing, and storing data for analytical and operational use cases.  Essential Duties and Responsibilities:  Create and maintain technical design documentation.  Conduct requirements gathering, data mapping and designing. Create, build, and maintain complex data pipelines from disparate sources that meet functional / non-functional business requirements. Create, maintain, and refine existing ETL/ELT processes, employing a variety of data integration and data preparation tools. Develop event-based, real-time, and micro-batch data pipelines. Design and implement high-frequency data science model results for operational purposes. Mentor engineers in finding optimal and efficient solutions for designing, preparing, and storing data for analytical and operational use cases.  Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing pipelines for greater scalability, etc. Work with stakeholders including Product, Data and Business teams to assist with data-related technical issues and support their data needs. Create datasets for: (1) operational reports, key performance indicators/metrics, or other insights into current organizational activities, (2) analytics and data science to provide the ability to uncover the answers to major questions that help organizations make objective decisions and/or gain a competitive edge. Write, debug, and implement complex queries involving multiple tables or databases across platform(s) Collaborate with the Enterprise Architecture team to ensure alignment on data standards and processes. Work with data and analytics experts to strive for greater functionality in data systems.  Position requires on-call and off-hours support.  Qualifications, Knowledge and Skills: Bachelor of Science in Computer Science, Information Technology, Data Science, Analytics or equivalent. 3+ years of experience in a data engineering or related role. 3+ years of experience with Python, SQL, and Command Line Interfaces. 3+ years of experience with streaming technologies (Kafka, Pubsub, Kinesis) and log-based architectures and experience writing batch and stream processing jobs (i.e. Apache Beam, Google Cloud DataFlow, Apache Spark, Apache Storm). 3+ years of experience working and creating datasets for a data warehouse. Clear understanding of data modeling patterns. 3+ years of experience with ETL/ELT development tools (Azure Data Factory (ADF) preferred). 3+ years of experience with code version control using tools, such as Git, and experience with Agile tools (Jira or Azure DevOps preferred). 3+ years of cloud experience (Azure preferred). Experienced in using best practices in designing, building and managing data pipelines that require data transformations as well as metadata and workload management. Experienced in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional and new data integration technologies (such as ETL, ELT, data replication, change data captures, message-oriented data movement, API design, stream data integration and data virtualization) Experienced with implementing data quality frameworks. Expert level knowledge with programming languages including Python, SQL, CLI. Expert level knowledge with relational SQL databases such as Oracle and SQL Server. Experience with ERP systems are a plus. Experience with NoSQL databases are a plus. Knowledge of the hospitality industry is a plus. Experience supporting and working with cross-functional teams in a dynamic environment.  Proven ability to collaborate with technical peers.  Capable of working independently as well as part of a team. Strive to provide orientation and direction to junior engineers requiring their expertise. Experienced with continuous integration and continuous deployment practices. Ability to approach complex problems with creativity and display analytical and problem-solving skills. Display curiosity in understanding the data for the specific area of responsibility.

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