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Amazon Data Engineer Jobs in Denver, CO (NOW HIRING)

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Amazon Data Engineer information

See Denver, CO salary details

$45.8K

$133.5K

$182.7K

How much do amazon data engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for amazon data engineer in Denver, CO is $133,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,900.00 and $141,500.00 per year, depending on experience, location, and employer.

What is an Amazon data engineer?

An Amazon Data Engineer is responsible for designing, building, and maintaining data infrastructure to support business intelligence and analytics. They work with large-scale datasets, optimize data pipelines, and ensure efficient data processing. Engineers collaborate with data scientists, analysts, and software teams to enable data-driven decision-making. Key skills include SQL, Python, ETL development, and experience with AWS services like Redshift, S3, and Glue.

What do Amazon data engineers do?

As an Amazon Data Engineer, you can expect to work on projects involving the design, development, and maintenance of large-scale data pipelines and data warehouses. Common challenges include optimizing data flows for efficiency, handling massive and complex datasets, and ensuring data quality and integrity across various sources. You'll frequently collaborate with data scientists, analysts, and other engineering teams to create scalable solutions that support business intelligence and machine learning initiatives. The fast-paced environment provides opportunities to solve unique technical problems and drive data-driven decision-making across Amazon’s diverse businesses.

What are the key skills and qualifications needed to thrive as an Amazon data engineer?

To thrive as an Amazon Data Engineer, you need strong proficiency in data modeling, ETL development, SQL, and programming languages such as Python or Java, typically accompanied by a degree in computer science or a related field. Familiarity with AWS cloud services (like Redshift, S3, and Glue), big data tools, and relevant certifications such as AWS Certified Data Analytics are highly valued. Strong problem-solving skills, effective communication, and the ability to work collaboratively in cross-functional teams set standout candidates apart. These skills and qualities ensure data is accurately managed, integrated, and made accessible for analytics and business decisions in Amazon's complex environment.

Is an Amazon Data Engineer in demand?

Amazon Data Engineers are in high demand due to the company's extensive data infrastructure needs, with skills in cloud platforms like AWS, data pipelines, and SQL being highly sought after. The role offers strong job growth prospects as organizations increasingly rely on data-driven decision making.

What are the most commonly searched types of Amazon Data Engineer jobs in Denver, CO?

The most popular types of Amazon Data Engineer jobs in Denver, CO are:

What are popular job titles related to Amazon Data Engineer jobs in Denver, CO?

For Amazon Data Engineer jobs in Denver, CO, the most frequently searched job titles are:

What job categories do people searching Amazon Data Engineer jobs in Denver, CO look for?

The top searched job categories for Amazon Data Engineer jobs in Denver, CO are:

Amazon Data Engineer jobs near you
Infographic showing various Amazon Data Engineer job openings in Denver, CO as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% Hybrid, and 50% Remote job distribution, with an average salary of $133,514 per year, or $64.2 per hour.

AWS Data Engineer | Big Data & Cloud Data Engineer

Long Finch Technologies

Littleton, CO • On-site

$115K - $138K/yr

Full-time

This job post has expired 2 days ago. 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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