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Aws Cloud Data Engineer Jobs (NOW HIRING)

Sarian, Inc.

AWS Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Role: Sr. AWS Cloud Data Engineer Location: Minneapolis, MN 55401 - Fulltime Position Must Have Technical/Functional Skills: * Data engineering background and hands-on work experience building data ...

Stellent IT LLC

Cloud Data Engineer

Nottingham, MD · On-site

$116K - $139K/yr

Cloud Data Engineer Nottingham, Maryland(Hybrid, 2 3 days on-site / week) Phone + SKype Visa : USC ... Manage the AWS Cloud infrastructure, in particular, compute and storage services (EC2, S3 ...

Navtech, Inc.

Cloud Data Engineer

Woonsocket, RI · On-site +1

$53.50 - $71.50/hr

Cloud Data Engineer Work Location: Remote Duration: 12+ Months of Contract * Total IT exp of 5-12 ... Azure, AWS, and/or GCP certifications preferred. * Develop and implement technical efforts to ...

Diverse Lynx

AWS Cloud Data Lake Lead

Cambridge, VT · On-site

Diverse Lynx is seeking an AWS Cloud Data Lake Lead to manage a team of data scientists and ML engineers. The role involves defining data science operations strategy, architecting scalable ML ...

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How much do aws cloud data engineer jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for aws cloud data engineer in the United States is $62.89, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.63 per hour, depending on experience, location, and employer.

What are some common challenges AWS Cloud Data Engineers face when working with large-scale data pipelines?

AWS Cloud Data Engineers often encounter challenges such as optimizing data pipelines for both performance and cost, ensuring data quality and consistency across distributed systems, and managing security and compliance requirements. Collaborating closely with data scientists, analysts, and DevOps teams is essential to address these issues effectively. Staying current with AWS services and best practices is also crucial, as the cloud landscape evolves rapidly and new tools are frequently introduced.

What is an AWS Cloud Data Engineer?

An AWS Cloud Data Engineer is a technology professional who designs, builds, and manages data solutions using Amazon Web Services (AWS). Their primary responsibilities include developing data pipelines, managing databases, and implementing data storage and processing solutions in the cloud. They work with services like Amazon S3, Redshift, Glue, and EMR to enable efficient data collection, transformation, and analysis for organizations. AWS Cloud Data Engineers ensure data reliability, scalability, and security while optimizing performance and cost. This role often requires strong knowledge of cloud architecture, data modeling, and programming languages such as Python or SQL.

What are the key skills and qualifications needed to thrive as an AWS Cloud Data Engineer?

To thrive as an AWS Cloud Data Engineer, you need expertise in data engineering principles, cloud infrastructure, and proficiency with languages such as Python or SQL, often supported by a degree in computer science or a related field. Familiarity with AWS services like S3, Redshift, Glue, Lambda, and relevant certifications (e.g., AWS Certified Data Analytics) is highly valuable. Strong problem-solving, communication, and collaboration skills help you design scalable solutions and work effectively with cross-functional teams. These skills ensure you can architect robust data pipelines and leverage cloud technologies to support business intelligence and analytics goals.
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Aws Cloud Data Engineer jobs near you
Infographic showing various Aws Cloud Data Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $130,802 per year, or $62.9 per hour.

AWS Data Engineer | Big Data & Cloud Data Engineer

Long Finch Technologies

Wheat Ridge, CO • On-site

$121K - $146K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

We are 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. The ideal candidate will have strong experience building data pipelines, managing data platforms, and delivering enterprise-level analytics solutions.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines and architectures on AWS to support analytics, reporting, and operational workflows.
  • Develop ETL/ELT solutions using AWS services.
  • Build and manage cloud-based data lakes and data warehouse solutions using: Amazon S3, Amazon Athena, Amazon Redshift and Amazon RDS.
  • Design and implement scalable data architectures while ensuring data quality, security, and integrity.
  • Develop data processing workflows to support large-scale data ingestion and transformation.
  • Collaborate with data scientists, analysts, and business teams to curate and optimize production-ready datasets.
  • Monitor, troubleshoot, and improve data pipeline performance and reliability.
  • Work with DevOps tools and practices including Jenkins and Maven for deployment automation.
Required Experience & Skills
  • 7+ years of experience in Big Data Engineering, Data Engineering, or related roles.
  • Strong hands-on experience with AWS cloud services and Big Data technologies.
  • Experience designing, developing, and maintaining scalable data pipelines and cloud-based data architectures.
  • Proficiency in developing ETL/ELT pipelines using AWS services such as AWS Glue, Lambda, Kinesis, and Step Functions.
  • Experience building and managing data lakes and data warehouses using AWS services including S3, Athena, Redshift, and RDS.
  • Strong knowledge of data modeling, data integration, and ensuring data quality and integrity.
  • Experience working with Hadoop and other Big Data technologies.
  • Strong SQL skills with experience in databases such as Oracle 10g/11g/12c and SQL Server.
  • Experience with Unix/Linux environments and scripting.
  • Familiarity with DevOps tools such as Jenkins and Maven.
  • Experience with monitoring and logging tools such as Splunk is preferred.
  • Ability to collaborate with data scientists, analysts, and cross-functional teams to deliver production-ready data solutions.

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