1 day ago
Base Salary
$101k - $160k/yr
Responsibilities
- Design and implement ETL/ELT pipelines using Redshift, S3, Glue, EMR, and Lambda.
- Build dimensional data models and semantic layers for self-service analytics and GenAI tools.
- Develop automated data quality frameworks with monitoring, alerting, and anomaly detection.
- Optimize cluster performance, query execution, resource management, and infrastructure costs.
- Centralize data models, eliminate duplicate pipelines, and implement lifecycle management.
- Establish data engineering practices for version control, code reviews, testing, and documentation.
- Create AI-ready datasets and partner with BIEs, data scientists, and product teams on scalable data products.
Requirements
- At least 1 year of data engineering experience.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Experience with one or more query languages such as SQL, PL/SQL, DDL, MDX, HiveQL, or SparkSQL.
- Experience with one or more scripting languages such as Python, KornShell, or Scala.
- Preferred experience with big data technologies such as Hadoop, Hive, Spark, or EMR.
- Preferred experience with ETL tools such as Informatica, ODI, SSIS, BODI, or Datastage.
Benefits
- Amazon provides health insurance including medical, dental, vision, prescription, Basic Life and AD&D insurance, and optional supplemental life plans.
- Benefits include an employee assistance program, mental health support, medical advice line, flexible spending accounts, and adoption and surrogacy reimbursement coverage.
- Benefits include 401(k) matching, paid time off, parental leave, sign-on payments, and restricted stock units.
- The position is located in Seattle, Washington.
Tech Stack
Categories
Data Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.