AWS Data Engineer: Scalable Pipelines & Lakes

Quantum Technologies. LLC

Chicago (IL)

On-site

USD 120,000 - 170,000

Full time

9 hours ago
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Job summary

Quantum Technologies. LLC is seeking a talented AWS Data Engineer to design, develop, and maintain scalable data pipelines in the AWS cloud. You will collaborate with data scientists, analysts, and stakeholders to deliver robust data solutions.

Responsibilities include building ingestion pipelines, ETL/ELT processing, and end-to-end data platform architecture with a focus on data lakes and data warehouses. Strong AWS experience and coding skills are required.

Qualifications

  • Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent.
  • 5 years of AWS data lake/warehouse experience in large enterprises.
  • Strong programming experience with Python, Shell scripting, and SQL.
  • Solid experience with AWS services including Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, SQS, DynamoDB, CloudFormation, IAM, KMS, Secrets Manager.

Responsibilities

  • Design, build, and maintain scalable data pipelines and architectures on AWS.
  • Create data ingestion pipelines from on-prem to AWS and within AWS using AWS services.
  • Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources.
  • Architect end-to-end data solutions with data lakes and data warehouses on AWS.
  • Participate in architecture discussions for high-scale data engineering projects.
  • Perform hands-on development, unit testing, and code reviews to ensure best practices.

Skills

Python
Shell scripting
SQL

Education

Bachelor's degree in Computer Science / Engineering

Tools

AWS Glue
AWS Redshift
AWS S3
AWS Lambda
Amazon EMR
Amazon Kinesis
Amazon SQS
DynamoDB
CloudFormation
IAM
KMS
Secrets Manager
RDS
Aurora

Job description

Quantum Technologies. LLC is seeking a talented AWS Data Engineer to design, develop, and maintain scalable data pipelines in the AWS cloud. You will collaborate with data scientists, analysts, and stakeholders to deliver robust data solutions.

Responsibilities include building ingestion pipelines, ETL/ELT processing, and end-to-end data platform architecture with a focus on data lakes and data warehouses. Strong AWS experience and coding skills are required.

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