Data Engineer II, AMZL Orbit
Luxembourg, LUX
Amazon.com
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Do you want to be in the forefront of engineering big data solutions that takes Transportation models to the next generation? Do you have a solid analytical thinking, metrics driven decision making and want to solve problems with solutions that will meet the growing worldwide need? We are looking for top notch Data Engineers to be part of our world class Transportation Business Intelligence team. We are building real time analytical platforms using big data tools and AWS technologies like Hadoop, Spark, EMR, SNS, SQS, Lambda, Kinesis Firehose, DynamoDB Streams.
The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. He/she is an expert with data modeling, ETL design and business intelligence tools and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact. He/she is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), and enjoys working in a fast-paced and global team. It's a big ask, and we're excited to talk to those up to the challenge!
- 2-5 years of experience performing quantitative analysis, preferably for an Internet with large, complex data sources.
- Hands-on experience on Big data technologies and frameworks. Hive, Spark, Hadoop, SQL on Big Data, Redshift
- Experience in near real time analytics
- Experience with scripting languages i.e. Python, Perl, etc.
- Experience with ETL, Data Modeling, and working with large-scale datasets. Extremely proficient in writing performant SQL working with large data volumes
- Ability to manage competing priorities simultaneously and drive projects to completion.
- Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering).
- Experience with large scale data processing, data structure optimization and scalability of algorithms a plus
- Experience in data engineering
- Experience with data modeling, warehousing and building ETL pipelines
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. He/she is an expert with data modeling, ETL design and business intelligence tools and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact. He/she is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), and enjoys working in a fast-paced and global team. It's a big ask, and we're excited to talk to those up to the challenge!
- 2-5 years of experience performing quantitative analysis, preferably for an Internet with large, complex data sources.
- Hands-on experience on Big data technologies and frameworks. Hive, Spark, Hadoop, SQL on Big Data, Redshift
- Experience in near real time analytics
- Experience with scripting languages i.e. Python, Perl, etc.
- Experience with ETL, Data Modeling, and working with large-scale datasets. Extremely proficient in writing performant SQL working with large data volumes
- Ability to manage competing priorities simultaneously and drive projects to completion.
- Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering).
- Experience with large scale data processing, data structure optimization and scalability of algorithms a plus
Basic Qualifications
- Experience in data engineering
- Experience with data modeling, warehousing and building ETL pipelines
- Knowledge of distributed systems as it pertains to data storage and computing
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Big Data Jobs
Engineering Jobs
Tags: AWS AWS Glue Big Data Business Intelligence Computer Science Distributed Systems DynamoDB Engineering ETL Firehose Hadoop Kinesis Lambda Mathematics Perl Pipelines Privacy Python RDBMS Redshift Security Spark SQL Statistics
Region:
Europe
Country:
Luxembourg
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