Job Location: Arlington, VA
- Degree in Computer Science, Engineering, Mathematics, or a related field or 5+ years industry experience
- Data modeling and ETL development experience
- Data Warehousing Experience with Oracle, Redshift, Teradata, etc.
- Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
- Experience in programming languages (, , Perl, etc.)
- Query performance tuning skills using Unix profiling tools and SQL
Job summary
Are you interested in leveraging the latest AWS technologies, at-scale, to support cutting-edge Machine Learning? Are you someone who likes using big data to drive high-impact business decisions? Do you enjoy building data applications used worldwide by scientists, engineering teams, and business partners? If your answer is yes, join our team! The Prime Machine Learning and Economics team is the core science team within Amazon Prime. We build recommendation systems, simulation technology, and insight-driving data science to ensure Prime remains one of the world’s most loved membership programs. As part of our data engineering team, you will continually reinvent our data pipeline and engineering infrastructure. These systems form the backbone of our prediction and causal inference technology.
As a senior data engineer on this team, you will collaborate closely with Prime business leaders, scientists (economists, research scientists, applied scientists) and engineering leaders to build data solutions. You will leverage AWS technologies (EMR, EC2, S3, GLUE, KMS, Lambda, DynamoDB, etc.) to build novel systems and tackle challenges at scale. You will manipulate and process TB-sized data, supporting real-time access and orchestration across multiple systems. Your work will enhance our scientific models and data applications. As a consequence, you will have global impact, improving customer experiences for Prime members worldwide. As a successful candidate, you will successfully interact with both technical and business stakeholders.
Our team is unique for two reasons. First, it has a broad mandate to model customer behavior, given the reach of the Prime membership program (millions of members, world-wide). This mandate leads us to build models and data infrastructure that interact with those of other benefit teams (i.e. Prime Video, Groceries) or marketplace teams (e.g. EU, India, Japan). Second, we build cutting-edge customer-level simulations using a variety of statistical tools (ML/econometrics/causal inference). Supporting this simulation technology, at-scale and in real-time, creates interesting new data engineering challenges. These give a person in this role a head start in solving artificial intelligence challenges that will be ubiquitous 3-5 years from now.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit https://www.amazon.jobs/en/disability/us
- MS in a technical or business field
- Experience with AWS technologies including, EMR, Spark, S3 etc.
- Ability to deal well with ambiguity
- Strong sense of ownership, urgency, and drive
- Demonstrated ability to drive operational excellence and best practices.
- Excellence in technical communication with peers, partners, and non-technical cohorts
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit https://www.amazon.jobs/en/disability/us
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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