Data Engineer

Disney Experiences is seeking a Data Engineer to build AWS-based data ingestion pipelines and distributed data solutions for structured and unstructured data.

Responsibilities

• Design and develop data pipelines in AWS and Snowflake
• Design and develop data views; support architecture decisions, deployment, and feedback loops
• Develop and support data solutions using AWS services including CDK, CloudFormation, Kinesis, Lambda, SQS, SNS, S3, and EC2
• Debug and troubleshoot across a broad technical stack
• Provide product ownership and strong business support in an enterprise theme park related environment
• Work with multiple business partner groups across Disney Parks and Resorts to implement optimal technical solutions
• Perform data and system analysis to support feature engineering
• Develop and maintain data quality checks and validation processes to ensure reliable and accurate data assets
• Create ingestion pipelines including workloads and applications inside AWS
• Implement, troubleshoot, and optimize distributed solutions using technologies such as SQL, S3, Glue, MSK, Snowflake, and Redshift to solve large-scale processing problems in a Cloud DW environment
• Design syndicated and curated data views for reporting, analytics, and advanced applications
• Apply technical expertise and mathematical concepts to challenging programming problems

Requirements

• 3+ years of Data Engineering (or similar), supporting SQL in a Data warehouse environment
• Strong knowledge of Python and object-oriented programming
• Working experience with Snowflake native objects, including:
  • SnowPipe
  • external/internal stages
  • external tables
  • integration objects
  • stored procedures using Snowflake Scripting
  • stream & task
  • data masking
  • time travel and cloning
• Ability to design scalable dimensional and analytical data models for enterprise reporting, self-service analytics, and data product consumption
• Ability to translate business requirements into scalable data solutions and curated datasets
• Experience building data pipelines and complex data transformations
• Experience with AWS S3, Glue, MSK, Redshift, Spark, or related ETL/Deployment tools
• Working knowledge of Data Build Tool (DBT)
• Experience working in an Agile/Scrum development environment
• Conceptual understanding of security at rest and in transit for big data pipelines
• Strong troubleshooting and problem-solving skills to analyze and resolve data and system issues
• Hands-on experience implementing data pipelines and data models within established architectural frameworks
• Strong systems and data analysis skills, including experience with testing in data
• Experience with CI/CD pipelines and source control tools such as GitHub

Technology Stack

• AWS, Snowflake, SQL, Python
• S3, Glue, MSK, Redshift, Spark
• CDK, CloudFormation, Kinesis, Lambda, SQS, SNS, EC2
• SnowPipe, external/internal stages, external tables
• integration objects, stored procedures (Snowflake Scripting)
• stream & task, data masking, time travel, cloning
• Data Build Tool (DBT), Agile/Scrum
• CI/CD pipelines, GitHub

Preferred Qualifications

• Experience with Airflow or other workflow orchestration tools
• Experience supporting real-time data processing workloads
• Familiarity with data governance, metadata management, and data lineage concepts
• Exposure to machine learning or analytics use cases
• Experience working with large-scale cloud-based data platforms

Education

• Bachelor's degree in computer science, Distributed Computing, Machine Learning, Mathematics or related field

Benefits

• health and savings benefits
• educational opportunities
• special extras that only Disney can provide

Location & Compensation

• Orlando, FL (onsite)
• USD 101,800 - 136,500 per year
• Hiring range reflects Orlando base pay: $101,800.00-$136,500.00 per year
• Base pay offered may vary based on internal equity, geographic region, and job-related knowledge, skills, and experience
• Bonus and/or long-term incentive units may be provided, plus medical, financial, and/or other benefits based on level and position offered

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