Data Engineer
Seattle, Washington, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...As a Data Engineer you will enable data-driven decision making within the Amazon Web Services Data Center Infrastructure Operations organization. The Infrastructure Operations Team is responsible for planning, implementing, monitoring and continuously improving the global Amazon Data Center infrastructure. The team supports all aspects of the Data Center based organizations, including but not limited to : Safety, Security, maintenance, daily operations, logistics, engineering and equipment management.
You will be developing, implementing and maintaining the information data lake and utilizing insight platforms to enable decision support systems for the overall organization. You should have excellent business and communication skills, and be able to work with business owners to understand their data and reporting requirements.
Above all, you should be passionate about working with huge data sets and be someone who is able to bring data sets together to answer business questions and drive growth. You will build ETLs to ingest the data into the data warehouse and data lake, as well as end-user facing reporting applications. You will primarily support teams within the Infrastructure environment, but will also have opportunities to support teams in the overall Amazon Web Services community.
You will work with business customers and development teams to define analytics requirements and then deliver flexible, scalable, end-to-end solutions.
You will have an opportunity to work with big data and emerging technologies while driving business intelligence solutions end-to-end: business requirements, data modeling, ETL, metadata, reporting, and dashboarding. You should have expertise in the design, creation, management, and business use of large datasets.
Basic Qualifications
- Bachelor’s Degree in Computer Science, Information Systems, Mathematics, Statistics, or related field
- 6+ years of experience in Data engineering
- 4+ years of experience with Data modeling, SQL, ETL , Data Warehousing and Datalakes
- 4+ years experience in writing SQL scripts Expert knowledge in an enterprise class RDBMS
- Experience with scripting language such as Python, Perl, Ruby or Javascript
- Excel in the design, creation, and management of very large datasets
Preferred Qualifications
- Ability to balance and prioritize multiple conflicting requirements with high attention to detail.
- Excellent verbal/written communication & data presentation skills, including ability to succinctly summarize key findings and effectively communicate with both business and technical teams.
- Comfortable working in a Linux environment
- Experience with MPP databases such as Redshift
- Knowledge of AWS products and services
- Exposure to predictive/advanced analytics and tools (such as R, SAS, Matlab)
- Experience with Datalake development
- Exposure to noSQL databases (such as DynamoDB, MongoDB)
- Meets/exceeds Amazon’s leadership principles requirements for this role
- Meets/exceeds Amazon’s functional/technical depth and complexity for this role
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Big Data Business Intelligence Computer Science Data Warehousing DynamoDB Engineering ETL Excel JavaScript Linux Mathematics Matlab MongoDB MPP NoSQL Perl Python R RDBMS Redshift Ruby SAS Security SQL Statistics
Perks/benefits: Flex hours
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open Marketing Data Analyst jobs
- Open MLOps Engineer jobs
- Open Junior Data Scientist jobs
- Open AI Engineer jobs
- Open Data Engineer II jobs
- Open Senior Data Architect jobs
- Open Sr Data Engineer jobs
- Open Senior Business Intelligence Analyst jobs
- Open Data Analytics Engineer jobs
- Open Power BI Developer jobs
- Open Manager, Data Engineering jobs
- Open Product Data Analyst jobs
- Open Principal Data Engineer jobs
- Open Business Data Analyst jobs
- Open Data Quality Analyst jobs
- Open Data Manager jobs
- Open Sr. Data Scientist jobs
- Open Data Scientist II jobs
- Open Big Data Engineer jobs
- Open Business Intelligence Developer jobs
- Open Data Analyst Intern jobs
- Open Principal Data Scientist jobs
- Open ETL Developer jobs
- Open Azure Data Engineer jobs
- Open Data Product Manager jobs
- Open Business Intelligence-related jobs
- Open Data quality-related jobs
- Open Privacy-related jobs
- Open Data management-related jobs
- Open GCP-related jobs
- Open Java-related jobs
- Open ML models-related jobs
- Open Finance-related jobs
- Open Data visualization-related jobs
- Open Deep Learning-related jobs
- Open APIs-related jobs
- Open PyTorch-related jobs
- Open PhD-related jobs
- Open Consulting-related jobs
- Open TensorFlow-related jobs
- Open Snowflake-related jobs
- Open NLP-related jobs
- Open Data warehouse-related jobs
- Open Data governance-related jobs
- Open Airflow-related jobs
- Open Hadoop-related jobs
- Open Databricks-related jobs
- Open LLMs-related jobs
- Open DevOps-related jobs
- Open Kubernetes-related jobs