AWS Data Engineer: Pipelines, Lakes & Analytics

Pb Consulting; Golden (CO); On-site; USD 130,000 - 170,000; Full time

Job summary

Pb Consulting is seeking an experienced AWS Data Engineer / Big Data Technology Lead to design, develop, and maintain scalable data solutions using AWS cloud technologies and big data frameworks. You will build data pipelines, manage data platforms, and deliver enterprise analytics solutions across complex environments.

The role focuses on ETL/ELT development, data lake/warehouse architecture, and collaboration with data scientists, analysts, and business teams to deliver production-ready

Qualifications

• 7+ years of experience in Big Data/Data Engineering roles.
• Strong hands-on experience with AWS cloud services and Big Data tech.
• Experience designing and maintaining scalable data pipelines and cloud-based architectures.

Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures on AWS.
• Develop ETL/ELT solutions using AWS services.
• Build and manage cloud-based data lakes and data warehouses (S3, Athena, Redshift, RDS).
• Ensure data quality, security, and integrity in data architectures.
• Develop data processing workflows for large-scale ingestion and transformation.
• Collaborate with data scientists, analysts, and business teams on production-ready datasets.
• Monitor and optimize data pipeline performance and reliability.
• Work with DevOps practices and deployment automation (Jenkins, Maven).

Skills

Big Data Engineering

AWS cloud services

ETL/ELT pipelines

Data lakes/warehouses

SQL

Unix/Linux scripting

DevOps tools (Jenkins/Maven)

Data modeling/quality

Hadoop

Tools

Jenkins

Maven

Lambda

Kinesis

Glue

Athena

Redshift

S3

Job description

Pb Consulting is seeking an experienced AWS Data Engineer / Big Data Technology Lead to design, develop, and maintain scalable data solutions using AWS cloud technologies and big data frameworks. You will build data pipelines, manage data platforms, and deliver enterprise analytics solutions across complex environments.

The role focuses on ETL/ELT development, data lake/warehouse architecture, and collaboration with data scientists, analysts, and business teams to deliver production-ready