Senior Data Engineer

Senior Data EngineerAbout the Role & Team:We Power the Magic!" That's our motto at Disney Experiences Technology (DXT). Our team creates world-class immersive digital experiences for the Company's premier vacation brands. We deliver experiences to consumers through our Disney's Parks & Resorts worldwide, Disney Cruise Lines, and Disney Vacation Club.We are responsible for the end-to-end digital and physical Guest experience for all technology & digitally led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation and Merchandise lines of business, as well as other initiatives such as Hey, Disney!If you're passionate about building the platforms and frameworks that power data at scale, come join us! We're seeking a Senior Data Engineer to help build and operate a near-real-time data streaming platform that makes delivering guest data products faster, more reliable, and more efficient across Disney Experiences. Data streams continuously from many source systems and must be processed and served with low latency to keep Guest experiences up-to-date and accurate. Your focus will be building reusable platform capabilities, frameworks, and tooling that enable teams to deliver data products through configuration rather than custom engineering. This includes designing and optimizing pipelines, transformations, and data assets to convert raw data into reliable, consumable products, while ensuring platform reliability, data quality, and freshness.This role sits in the Data Platform and Products (DPP) organization within Technology for Disney Experiences.The Senior Data Engineer will report to the Manager, Data Engineering.This is a full-time role.What You'll Do/ Key Responsibilities:Contribute to the design, building, and supervision of technology architecture, solutions, and software dedicated to capturing, managing, and using both structured and unstructured data from various sourcesDevelop efficient processes and structures to streamline data flow, routing, and storage, adhering to both business and technical specifications, and leveraging cloud and local storage options as requiredApply technical tools and programming skills for the purposes of data cleansing, organization, transformation, and upkeep, integrating automation and advanced methodologies such as big data, artificial intelligence, and machine learningUphold design standards and quality assurance protocols for the development of software and systems, ensuring seamless data compatibility, functionality, and integrity across all data connections, transmissions, and storage platformsEvaluate internal and external business and product requirements to ensure alignment of data operations and endeavors with overarching organizational objectives and prioritiesDevelop data pipelines and shared monitoring infrastructure that power observability, pipeline health, and data quality for the broader teamCreate infrastructure data products (cost tracking, resource utilization, audit logs)You will be expected to stay up to date with emerging technologiesMay be required to provide support escalation, oversee the ongoing operations, and support the enhancement of existing tools as neededRequired Qualifications & Skills:Minimum 5 years of Data Engineering, Software Development or similar experience required.Proficiency in fundamentals of data pipelining, ELT/ETL processes, data architecture, and the overall data lifecycle, complemented by hands-on experience in designing and implementing efficient data workflows and processesDemonstrating ability to contribute across multiple phases of development for complex projects, including technical design, implementation, and end-to-end testing, ensuring the successful delivery of data engineering solutionsPassionate about delivering data engineering projects collaboratively, with a strong commitment to achieving team goalsEffective troubleshooting skills, capable of identifying and resolving sophisticated issues with sound judgment and initiativeComfortable working in an agile environment, with prior experience in Agile and Scrum methodologies, ensuring adaptability to evolving project requirements and effective collaboration with cross-functional teamsProficiency in SQL, Python, AWS services (e.g. IAM, S3, Kinesis Data Stream, Kinesis Firehose, Lambda, DynamoDB, DMS, EventBridge), with a proactive demeanor towards continuous learning and skill development, and an interest in mastering emerging data engineering tools and methodologiesExperience working across both relational and NoSQL databases (e.g., Snowflake, DynamoDB, Redis, MongoDB), with the ability to optimize data structures and storage choices for performance and scalabilityPreferred Qualifications:Expertise coding and developing solutions that solve complex problems, while keeping in mind code space and time complexityProficiency in DevOps practices, e.g.: CI/CD, docker, testing, and automationUnderstanding of trade-offs between different data storage systems and architectures (data warehouses, SQL vs NoSQL, partitioning, etc.)Knowledge of DevOps conceptsExperience with API development (e.g., RESTful services, API design, authentication) for exposing and consuming data products and services resiliently, performantly, and at scaleExperience developing real-time data processing using Apache Flink, or comparable stream-processing frameworks (e.g., Spark, Kafka, or Apache Beam)Experience with infrastructure-as-code, e.g.: Terraform, CloudFormation, AWS CDK, etc.Required Education:Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience required