Senior Data Engineer, ADE Science
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Monthly Salary:
Posted on:
12 hours ago
Vacancies:
1 Vacancy
Department:
Job Summary
The Alexa Daily Essentials team delivers experiences critical to how customers interact with Alexa as part of daily life. Alexa users engage with our products across experiences connected to Timers Alarms Calendars Food and News. Our experiences include critical time saving techniques ad-supported news audio and video and in-depth kitchen guidance aimed at serving the needs of the family from sunset to sundown.
As a Data Engineer on this team you will built data pipeline and analytics solutions for our internal customers to answer question with data drive critical business decisions and product quality improvements for our customers. Our Data Engineers use best practices in software engineering data management data storage and compute. You will work on a cross-functional team with other data engineers and scientists and drive changes that directly impact our customers.
Key job responsibilities
Data Infrastructure
- Architect and develop robust data pipelines that ingest and transform data for business intelligence analytics
- Maintain data pipelines using scripting languages such as Python Spark SQL and AWS services such as S3 Glue Lambda SNS SQS KMS
- Design and implement scalable data infrastructure supporting Redshift clusters and visualization dashboards that serve product stakeholders
- Build self-serve data platforms to enable scientists and business stakeholders to answer business questions with data. Implement and support reporting and analytics infrastructure for internal customers.
- Ensure compliance with data governance. Address data access restrictions while maintaining adherence to data protection policies and security standards
- Implement data quality monitoring mechanisms with alerting for pipeline failures or anomalies. Ensure data and reporting consistency across the organization
Communication
- Excel at communicating complex ideas to technical and non-technical audiences.
- Build relationships with product and engineering stakeholders and counterparts.
- Work with stakeholders to gather requirements and translate business needs into data engineering solutions
- Work cross-functionally across product and engineering teams to drive adoption of data assets
Operations
- Drive automation and operational excellence in data infrastructure. Reduce manual intervention and improve system reliability.
- Scale existing solutions. Create new solutions as required based on team and stakeholder needs.
- 5 years of data engineering experience
- Experience with data modeling warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
- Experience mentoring team members on best practices
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience operating large data warehouses
- Experience communicating with users other technical teams and management to collect requirements describe data modeling decisions and data engineering strategy
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary for this position ranges from $135700/year up to $226500/year. Salary is based on a number of factors 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. Applicants should apply via our internal or external career site.
As a Data Engineer on this team you will built data pipeline and analytics solutions for our internal customers to answer question with data drive critical business decisions and product quality improvements for our customers. Our Data Engineers use best practices in software engineering data management data storage and compute. You will work on a cross-functional team with other data engineers and scientists and drive changes that directly impact our customers.
Key job responsibilities
Data Infrastructure
- Architect and develop robust data pipelines that ingest and transform data for business intelligence analytics
- Maintain data pipelines using scripting languages such as Python Spark SQL and AWS services such as S3 Glue Lambda SNS SQS KMS
- Design and implement scalable data infrastructure supporting Redshift clusters and visualization dashboards that serve product stakeholders
- Build self-serve data platforms to enable scientists and business stakeholders to answer business questions with data. Implement and support reporting and analytics infrastructure for internal customers.
- Ensure compliance with data governance. Address data access restrictions while maintaining adherence to data protection policies and security standards
- Implement data quality monitoring mechanisms with alerting for pipeline failures or anomalies. Ensure data and reporting consistency across the organization
Communication
- Excel at communicating complex ideas to technical and non-technical audiences.
- Build relationships with product and engineering stakeholders and counterparts.
- Work with stakeholders to gather requirements and translate business needs into data engineering solutions
- Work cross-functionally across product and engineering teams to drive adoption of data assets
Operations
- Drive automation and operational excellence in data infrastructure. Reduce manual intervention and improve system reliability.
- Scale existing solutions. Create new solutions as required based on team and stakeholder needs.
- 5 years of data engineering experience
- Experience with data modeling warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
- Experience mentoring team members on best practices
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience operating large data warehouses
- Experience communicating with users other technical teams and management to collect requirements describe data modeling decisions and data engineering strategy
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary for this position ranges from $135700/year up to $226500/year. Salary is based on a number of factors 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. Applicants should apply via our internal or external career site.
Required Experience:
Senior IC
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
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