Amazon Data Engineer - People Analytics 

United States, California, San Francisco 

184816246

About the RoleAs the Data Engineer in the People & Places organization, you will be responsible for building and managing the core data pipelines and analytics tooling that power critical HR reporting functionality. This highly sensitive work requires the utmost care and discretion to ensure the security and integrity of confidential employee data as you develop the systems that HR relies on for important decision-making. Your role will involve partnering closely with an Analyst and Program Manager to design, implement, and optimize a robust data infrastructure to support the organization's talent management and workforce analytics initiatives.You Will
- Develop and manage scalable data pipelines to extract, transform, and load HR data from various sources
- Ensure the security, reliability, and performance of the data infrastructure
- Collaborate with stakeholders to understand business requirements and translate them into data-driven solutions
- Automate data processing and reporting workflows to improve efficiency and data integrity
- Implement data quality checks and monitor processes to maintain high data accuracy

- 2+ years of experience working in a data engineering or software engineering capacity
- Extensive experience in developing and optimizing data pipelines using Python
- Proficient in working with AWS services such as EMR, Redshift, Glue, and S3
- Demonstrates expertise in schema management, data lineage, and auditability, coupled with a strong command of data modeling, ETL processes, and data warehousing principles
- Proven experience implementing data integrity practices in ETL/ELT pipelines, ensuring accuracy, consistency, and reliability

- Proven experience implementing data integrity practices in ETL/ELT pipelines, ensuring accuracy, consistency, and reliabilityPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.