We are looking for passionate data engineers to optimize the consumption of very large data sources we require to generate unique insights. As a data engineering leader within Alexa, we look to you for design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work.
- Can create coherent Logical Data Models that drive physical design.
- Collaboration with colleagues from multidisciplinary science, engineering and business backgrounds.
- Delivers pragmatic solutions. You do things with the proper level of complexity the first time (or at least minimize incidental complexity).
- Has knowledge of recent advances in distributed systems (e.g. MapReduce, MPP architectures, and NoSQL databases). You are proficient in a broad range of data design approaches and know when it is appropriate to use them (and when it is not).
- Understands how to be efficient with resource usage (e.g., system hardware, data storage, query optimization, AWS infrastructure etc.)
- Works with engineers to develop efficient data querying and modeling infrastructure.
- Knowledge of engineering and operational excellence best practices. Can make enhancements that improve data processes (e.g., data auditing solutions, management of manually maintained tables, automating, ad-hoc or manual operation steps).
- Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions
- Understands how to make appropriate data trade-offs. Can balance customer requirements with technology requirements. Knows when to re-use code. Is judicious about introducing dependencies.
- Writing code that a Data Engineer or Software Development Engineer unfamiliar with the system can understand.
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience working as an Analytics Engineer or Data Scientist working with cross functional teams.
- Experience working with enterprise reporting systems, data analytics.
- Bachelor’s degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering)
- Experience in data modeling, ETL development, and Data warehousing
- 3+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets
- Experience with cloud data platforms and big data solutions
- Experience with Tableau, Matillion, and AWS services (Redshift, S3, AWS Glue, EMR, DynamoDB)
- 3+ years of relevant experience in one of the following areas: Data engineering, database engineering, business intelligence or business analytics
- Master’s degree in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering)
- Demonstrable experience in scripting languages (Python, Perl, Ruby) and Excel
- Experience with massively parallel processing (MPP) databases (data warehouse and data lake)
Vacancy Type: Full Time
Job Location: Cambridge, MA, US
Application Deadline: N/A