At Audible, the business problem is to design and build the paths to fine-tune operations and outpace competitors through data-driven innovation, by leveraging the Data Engineering group to own datasets and platforms that enable systems and people to uncover new insights.
Requirements
- Proficiency in functional programming languages (e.g. Python) as well as declarative programming languages (e.g. SQL, SPARQL)
- Experience processing and modeling large, complex data sets for Analytical use cases with Database technologies such as AWS Redshift, Teradata or equivalent
- Familiarity with AWS cloud technologies such as Elastic Map Reduce (EMR), Kinesis, Athena
- Familiarity with BI and Visualization platforms such as MicroStrategy and AWS Quicksight
- Experience with React, HTTP/2, Serverless, Microservices, and cross-platform development
- Prior use of AWS technologies at scale in a production environment
- Working knowledge of Machine Learning techniques
Responsibilities
- Develop and maintain ETL pipelines and data processing systems under guidance from senior team members
- Implement data models and transformations based on established patterns and requirements
- Write clean, testable code following team standards and best practices
- Collaborate with team members on data pipeline design and implementation
- Participate in code reviews and learn from feedback to improve technical skills
- Support data quality initiatives and monitoring of existing systems
- Document work and contribute to team knowledge sharing
Other
- Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Physics, or a related field
- Ability to communicate effectively and work independently with little supervision to deliver on time quality products
- Willingness to learn, be open minded to new ideas and different opinions yet knowing when to stop, analyze, and reach a decision
- Strong problem-solving skills, adaptable, proactive and willing to take ownership
- Passion for data, coding, modeling, research design and cutting-edges algorithms
