Data Engineer, PXT Central Science
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Job Location:
Arlington, TX - USA
Yearly Salary:
$ 118900 - 205600
Posted on:
27 days ago
Vacancies:
1 Vacancy
Department:
Job Summary
The PXT Central Science team is looking for a Data Engineer. This individual will join a team of economists and scientists to own and accelerate science and analytics in our rapid employee intelligence workstream. This suite of models identifies causal factors driving changes in employee sentiment actions and business outcomes.
Key job responsibilities
We are looking for a data engineer with expertise in complex data environments. You will be responsible for enhancing our existing data architecture to further standardize metrics and definitions building and testing new features developing end-to-end data engineering solutions for complex analytical problems and collaborating with economists data scientists and software engineers to translate data into actionable insights. Specific responsibilities include:
- Data Pipeline Development & Management: Design and maintain scalable data pipelines using native AWS services (Glue EMR Lambda); Build robust monitoring and error handling systems for data workflows; Optimize pipeline performance reliability and cost efficiency; Develop feature engineering frameworks and automated data transformations; Create clear documentation for pipeline architecture and operations
- Advanced Data Integration: Design and implement pipelines for diverse data types (text image audio); Build scalable feature extraction and processing frameworks; Develop robust data quality and validation checks; Create flexible schemas to support evolving data requirements; Shape data strategy and modeling approaches across teams
- Cross-team Collaboration: Partner with economics and data science teams to understand analytical requirements; Work closely with software engineering teams to ensure seamless integration with existing systems; Collaborate with infrastructure teams to optimize resource utilization across interconnected AWS accounts; Participate in technical design reviews and architecture discussions.
- Analytics Platform Management: Maintain and enhance layered data systems used by economists and scientists; Build automated reporting solutions for senior leadership and other stakeholders; Implement version control and change management processes for analytical environments.
- Technical Environment: Work across multiple interconnected AWS accounts and services; Implement security best practices for cross-account data access; Design solutions that scale across multiple regions and business units.
About the team
The Central Science Team within Amazons People Experience and Technology org (PXTCS) uses economics behavioral science statistics machine learning and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives well-being and the value of work to Amazonians. We are an interdisciplinary team which combines the talents of science engineering and UX to develop and deliver solutions that measurably achieve this goal.
- Knowledge of professional software engineering & best practices for full software development life cycle including coding standards software architectures code reviews source control management continuous deployments testing and operational excellence
- 3 years of data engineering experience
- Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
- Experience with data modeling warehousing and building ETL pipelines
- 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)
- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience architecting/operating solutions built on AWS
- Experience communicating with users other technical teams and management to collect requirements describe software product features and technical designs
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118900/year in our lowest geographic market up to $205600/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Key job responsibilities
We are looking for a data engineer with expertise in complex data environments. You will be responsible for enhancing our existing data architecture to further standardize metrics and definitions building and testing new features developing end-to-end data engineering solutions for complex analytical problems and collaborating with economists data scientists and software engineers to translate data into actionable insights. Specific responsibilities include:
- Data Pipeline Development & Management: Design and maintain scalable data pipelines using native AWS services (Glue EMR Lambda); Build robust monitoring and error handling systems for data workflows; Optimize pipeline performance reliability and cost efficiency; Develop feature engineering frameworks and automated data transformations; Create clear documentation for pipeline architecture and operations
- Advanced Data Integration: Design and implement pipelines for diverse data types (text image audio); Build scalable feature extraction and processing frameworks; Develop robust data quality and validation checks; Create flexible schemas to support evolving data requirements; Shape data strategy and modeling approaches across teams
- Cross-team Collaboration: Partner with economics and data science teams to understand analytical requirements; Work closely with software engineering teams to ensure seamless integration with existing systems; Collaborate with infrastructure teams to optimize resource utilization across interconnected AWS accounts; Participate in technical design reviews and architecture discussions.
- Analytics Platform Management: Maintain and enhance layered data systems used by economists and scientists; Build automated reporting solutions for senior leadership and other stakeholders; Implement version control and change management processes for analytical environments.
- Technical Environment: Work across multiple interconnected AWS accounts and services; Implement security best practices for cross-account data access; Design solutions that scale across multiple regions and business units.
About the team
The Central Science Team within Amazons People Experience and Technology org (PXTCS) uses economics behavioral science statistics machine learning and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives well-being and the value of work to Amazonians. We are an interdisciplinary team which combines the talents of science engineering and UX to develop and deliver solutions that measurably achieve this goal.
- Knowledge of professional software engineering & best practices for full software development life cycle including coding standards software architectures code reviews source control management continuous deployments testing and operational excellence
- 3 years of data engineering experience
- Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
- Experience with data modeling warehousing and building ETL pipelines
- 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)
- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience architecting/operating solutions built on AWS
- Experience communicating with users other technical teams and management to collect requirements describe software product features and technical designs
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118900/year in our lowest geographic market up to $205600/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
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