At Amazon, the Leadership Principle "Strive to be Earth’s Best Employer" challenges us to create "a safer, more productive, higher performing, more diverse, and more just work environment," and reinforces that nothing is more important than the safety and well-being of our teams, specifically within the Workplace Health and Safety (WHS) organization.
Requirements
- 2+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Responsibilities
- Architect and deliver enterprise-scale data infrastructure solutions, enabling robust dataset management and advanced business intelligence capabilities
- Build and orchestrate complex ETL processes across diverse data sources using SQL and AWS technologies, collaborating with cross-functional engineering teams
- Drive data architecture decisions through comprehensive technical documentation and evidence-based recommendations to stakeholder teams
- Streamline reporting workflows and implement automated solutions to enhance stakeholder self-service capabilities and operational efficiency
- Lead strategic initiatives with BI and technology partners to optimize data pipelines, improve data accessibility, and enhance infrastructure performance
- Learn and influence adoption of latest AWS technologies to expand platform capabilities and drive operational excellence
Other
- Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
