The Analytics Engineer will build the next generation of “big data” tools for Disney Parks, Experiences and Products translating a digital Guest experience into a magical real world Guest experience.
This role will work within a business-oriented DevOps culture and Agile environment, which seeks continuous improvement for big data analytics and business intelligence. More than a simple data plumber, the Analytics Engineer will be expected to investigate and implement innovation with tools like Pandas, Kafka, and SciPy to guide Analysts towards real-time insights.
The Analytics Engineer reports up to the Manager, Data Services and does not have direct reports.
- Develop data automation, accurately identify root cause of issues, supply quick defect fixes, and deploy solutions that match customer’s requests
- Regularly document changes and proactively updates progress in the request system
- Make suggestions on new approaches to drive adoption, efficiency, quality, or reliability
- Communicate effectively with technical and non-technical teams, in support of DPEP partners
- Follow corporate policies and laws regarding software development, data privacy and security (PCI, SOX, GDPR, etc)
- Independently learn new engineering practices to keep current with latest technology
- Strong problem solving and analysis skills
- Excellent written and verbal communications skills
- Experience in a big data environment (AWS Redshift, Google BigQuery, or Hadoop Hive/Impala)
- Experience with Java, Python, or R
- Experience with one or more DevOps tools such as Kubernetes, Jenkins, Maven, GitHub, Docker
- Experience with scripting in bash shell, PowerShell, Perl, or PHP
- Experience writing and editing SQL
- Understanding of Hadoop Ecosystem, MapReduce, Sqoop, and Data Partitioning
- Understanding of SDLC, Continuous Integration, QA and Agile Methodologies
- Understanding of JSON, XML, RESTful and SOAP services
- Experience with Cloudera Hadoop
- Strong understanding of NoSQL datastores and their applicable use cases
- Experience with ML frameworks such as TensorFlow, SparkMLlib, Apache Mahout, PySpark, Torch, Caffe, H2o, etc
- Bachelors Degree in technology field (Computer Science, Engineer, etc.)
- Masters Degree in technology field (Computer Science, Engineer, etc.)