Description
- 3+ years of data engineering experience
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with data modeling, warehousing and building ETL pipelines
- Experience working on and delivering end to end projects independently
- Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby
- Experience with Redshift, Oracle, NoSQL etc.
- 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)
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
As part of the Last Mile Science & Technology organization, you’ll partner closely with Product Managers, Data Scientists, and Software Engineers to drive improvements in Amazon's Last Mile delivery network. You will leverage data and analytics to generate insights that accelerate the scale, efficiency, and quality of the routes we build for our drivers through our end-to-end last mile planning systems. You will develop complex data engineering solutions using AWS technology stack (S3, Glue, IAM, Redshift, Athena). You should have deep expertise and passion in working with large data sets, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You will work with business owners to develop and define key business questions and requirements. You will provide guidance and support for other engineers with industry best practices and direction. Analytical ingenuity and leadership, business acumen, effective communication capabilities, and the ability to work effectively with cross-functional teams in a fast-paced environment are critical skills for this role.
Key job responsibilities
• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses.
• Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting
• Perform detailed source-system analysis, source-to-target data analysis, and transformation analysis
• Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance.
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with data modeling, warehousing and building ETL pipelines
- Experience working on and delivering end to end projects independently
- Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby
- Experience with Redshift, Oracle, NoSQL etc.
- 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)
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
As part of the Last Mile Science & Technology organization, you’ll partner closely with Product Managers, Data Scientists, and Software Engineers to drive improvements in Amazon's Last Mile delivery network. You will leverage data and analytics to generate insights that accelerate the scale, efficiency, and quality of the routes we build for our drivers through our end-to-end last mile planning systems. You will develop complex data engineering solutions using AWS technology stack (S3, Glue, IAM, Redshift, Athena). You should have deep expertise and passion in working with large data sets, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You will work with business owners to develop and define key business questions and requirements. You will provide guidance and support for other engineers with industry best practices and direction. Analytical ingenuity and leadership, business acumen, effective communication capabilities, and the ability to work effectively with cross-functional teams in a fast-paced environment are critical skills for this role.
Key job responsibilities
• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses.
• Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting
• Perform detailed source-system analysis, source-to-target data analysis, and transformation analysis
• Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance.
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