Data Engineer II: Scalable Data Pipelines & Analytics

Amazon Web Services (AWS); Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services (AWS) is seeking a Data Engineer to help build scalable data pipelines and infrastructure for our Global Sales & Operations teams. You will collaborate with ML engineers, BI engineers, and analysts to transform business questions into reliable data solutions that drive decision making.

You will design and implement ETL/ELT pipelines using SQL, Python, and AWS services like Redshift, S3, Glue, EMR, and Kinesis, while mentoring junior engineers and scaling existing systems.

Qualifications

• 3+ years of data engineering experience.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL.

Responsibilities

• Architect scalable, reliable data pipelines and infrastructure for analytics, reporting and operations.
• Design, develop and operate large-scale data structures for BI analytics.
• Build ETL pipelines using SQL, Python and AWS services like Data Pipelines, Glue.
• Apply best practices in data modeling to support online reporting and analysis.
• Mentor junior data engineers and collaborate with cross-functional teams.

Skills

Data engineering

ETL/ELT

OLAP

Data modeling

SQL

Tools

Redshift

S3

Glue

EMR

Kinesis

Lambda

IAM

Job description

Amazon Web Services (AWS) is seeking a Data Engineer to help build scalable data pipelines and infrastructure for our Global Sales & Operations teams. You will collaborate with ML engineers, BI engineers, and analysts to transform business questions into reliable data solutions that drive decision making.

You will design and implement ETL/ELT pipelines using SQL, Python, and AWS services like Redshift, S3, Glue, EMR, and Kinesis, while mentoring junior engineers and scaling existing systems.