Data Engineer II — AWS Data Pipelines & BI

D8 LooP

Bellevue (WA)

On-site

USD 120,000 - 160,000

Full time

2 days ago
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Job summary

AWS Infrastructure Services in Bellevue, WA is seeking a Data Engineer with 3+ years of experience to design and operate large-scale BI data structures. You will work with AWS Redshift, S3, Glue, EMR, Kinesis, and Lambda to build automated pipelines and dashboards, ensure data quality, and optimize cost and performance.

Join a team that moves operational data from manual processes to scalable, self-serve analytics environments.

Qualifications

  • 1+ years of developing and operating large-scale data structures for BI analytics.
  • Set and enforce data quality, freshness, and monitoring standards with alarms and runbooks.
  • SQL experience in developing and operating large-scale data structures for BI analytics.
  • Experience with AWS data services like Redshift, S3, Glue, EMR, Kinesis, Lambda, IAM.
  • Lead migration of manual, high-maintenance data processes to automated pipelines.
  • Cost and performance optimization across AWS data platforms.
  • Experience with Spark and streaming data in AWS stack.

Responsibilities

  • Migrate manual, high-maintenance data processes to automated pipelines.
  • Develop monitored data pipelines and dashboards that update automatically.
  • Collaborate across teams to optimize cost and performance while ensuring security.
  • Maintain data quality, freshness, and monitoring standards.

Skills

Data modeling
Data quality monitoring
SQL
Airflow orchestration
Dashboards automation
Cost & performance optimization
Leadership

Tools

AWS Redshift
AWS S3
AWS Glue
EMR
Kinesis
Lambda
IAM roles and permissions

Job description

AWS Infrastructure Services in Bellevue, WA is seeking a Data Engineer with 3+ years of experience to design and operate large-scale BI data structures. You will work with AWS Redshift, S3, Glue, EMR, Kinesis, and Lambda to build automated pipelines and dashboards, ensure data quality, and optimize cost and performance.

Join a team that moves operational data from manual processes to scalable, self-serve analytics environments.

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