ZipRecruiter

Log In

2

Remote Aws Data Engineer Jobs in Colorado (NOW HIRING)

Qode

AWS Data Engineer

CO · On-site +1

$114K - $137K/yr

Job Brief As an AWS Data Engineer, your role will be to design, develop, and maintain scalable data pipelines on AWS. You will work closely with technical analysts, client stakeholders, data ...

Qode

AWS Data Engineer

CO · On-site +1

$114K - $137K/yr

Job Brief As an AWS Data Engineer, your role will be to design, develop, and maintain scalable data pipelines on AWS. You will work closely with technical analysts, client stakeholders, data ...

Evio

Data Engineer (Remote)

Denver, CO · Remote

$117K - $141K/yr

Stay current with AWS services and recommend suitable tools for specific data engineering tasks.  ... Develop and support the internal applications using Python, SQL, and Stored Procedures.  ...

Viasat, Inc.

Data Engineer

Englewood, CO · On-site +1

$174K - $261K/yr

Our mission is to enable our community of data scientists, analysts, and developers to derive ... Familiarity with at least one cloud provider such as AWS, GCP, or Azure. * Experience in design and ...

Janus Henderson Investors

Data Engineer

Denver, CO · On-site +1

$169K/yr

Janus Henderson Investors US, LLC seeks a Data Engineer in Denver, CO responsible for the design ... Remote work permitted 2 days a week. Requirements: Bachelor's degree in Information Systems ...

DevIQ

Databricks Data Engineer

Denver, CO · On-site +1

$120K - $140K/yr

We are seeking a Databricks Data Engineer to join our growing team. In this role, you'll build ... Familiarity with cloud data platforms (e.g., Azure, AWS) * Solid understanding of ETL/ELT processes ...

DevIQ

Databricks Data Engineer

Denver, CO · On-site +1

We are seeking a Databricks Data Engineer to join our growing team. In this role, you'll build ... Familiarity with cloud data platforms (e.g., Azure, AWS) * Solid understanding of ETL/ELT processes ...

DSC Resources

Principal Data Engineering

Louisville, CO · Remote

$180K - $205K/yr

Remote Principal Software Engineer - Data Architecture and Engineering US-based only | No visa ... AWS, Azure, or GCP), including cost optimization · Experience with AI/LLM-assisted development ...

DISH Network LLC

Senior Data Engineer

Denver, CO · Remote

$147K - $158K/yr

Senior Data Engineer (Dish Wireless LLC, Littleton, Colorado) Multiple positions available. Design ... AWS (including S3, Athena, CloudWatch, Redshift, AppFlow, and CodeCommit), to collect, process ...

The Mutual Group

Lead AI Engineer - AWS Platform

Denver, CO · On-site +1

$130K - $190K/yr

Information Technology We are modernizing our data and analytics ecosystem by embedding AI and ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...

Forge Global

Senior Software Engineer I

Denver, CO · On-site +1

$189K - $200K/yr

The Role: As our Senior Data Engineer focusing on data engineering, you will play a crucial role ... This position is remote in Denver, CO. We intend to open an office in Denver and once we do, we ...

UDR

Senior Data Platform Engineer

Highlands Ranch, CO · Remote

$130K - $170K/yr

This is a remote based position.** GENERAL SUMMARY OF DUTIES: Design, build, and maintain UDR ... Experience with cloud platforms (AWS, Azure, or GCP) for data storage and processing preferred.

next page

Showing results 1-20

All JobsRemote Aws Data Engineer JobsRemote Aws Data Engineer Jobs in Colorado

Remote Aws Data Engineer information

See Colorado salary details

$46.8K

$136.4K

$186.6K

How much do remote aws data engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for remote aws data engineer in Colorado is $136,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,400.00 and $144,600.00 per year, depending on experience, location, and employer.

What is a Remote AWS Data Engineer?

A Remote AWS Data Engineer is a professional who designs, builds, and maintains data pipelines and architectures using Amazon Web Services (AWS) infrastructure, while working remotely. They are responsible for tasks such as data ingestion, transformation, storage, and ensuring data quality and security. AWS Data Engineers often work with services like Amazon S3, Redshift, Glue, Lambda, and EMR to enable scalable and efficient data processing. Their role is crucial in helping organizations manage and analyze large datasets in the cloud. Working remotely allows them to collaborate with teams from different locations using online tools and platforms.

What is the difference between Remote Aws Data Engineer vs Remote Cloud Data Engineer?

AspectRemote Aws Data EngineerRemote Cloud Data Engineer
CertificationsAWS Certified Data Analytics, AWS Certified Data Analytics - SpecialtyCloud certifications (AWS, Azure, GCP), relevant data certifications
Work EnvironmentPrimarily AWS cloud platform, data pipelines, ETL processesMultiple cloud platforms, data integration across services
Industry UsageTech, finance, healthcare using AWS infrastructureVaries across industries using multiple cloud providers
Search & Comparison IntentHigh overlap in skills, AWS-specific toolsBroader cloud skills, multi-platform focus

The Remote Aws Data Engineer specializes in AWS cloud services, focusing on data pipelines and analytics within the AWS ecosystem. In contrast, the Remote Cloud Data Engineer works across multiple cloud platforms, requiring broader cloud skills. Both roles involve data engineering but differ in platform expertise and certifications.

How does a remote AWS Data Engineer typically collaborate with cross-functional teams?

As a remote AWS Data Engineer, you'll often work closely with data scientists, analysts, and software engineers to design and maintain scalable data pipelines in the cloud. Collaboration usually happens through virtual meetings, cloud-based project management tools, and shared documentation platforms. Clear communication and proactive updates are essential to ensure everyone stays aligned, especially when troubleshooting data issues or implementing new features. Building strong working relationships remotely can be challenging, but most organizations support this with regular check-ins and team collaboration channels.

What are the key skills and qualifications needed to thrive as a Remote AWS Data Engineer, and why are they important?

To thrive as a Remote AWS Data Engineer, you need strong expertise in data engineering concepts, programming (such as Python or Scala), and experience with AWS cloud services like S3, Redshift, and Glue, typically supported by a relevant degree or AWS certification. Proficiency with ETL tools, data pipeline frameworks (e.g., Apache Airflow), and AWS-specific technologies is essential. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project delivery. These capabilities ensure scalable, secure, and efficient data solutions in distributed, cloud-based environments.
What are the most commonly searched types of Aws Data Engineer jobs in Colorado? The most popular types of Aws Data Engineer jobs in Colorado are:
What are popular job titles related to Remote Aws Data Engineer jobs in Colorado? For Remote Aws Data Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Aws Data Engineer jobs in Colorado look for? The top searched job categories for Remote Aws Data Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote Aws Data Engineer jobs? Cities in Colorado with the most Remote Aws Data Engineer job openings:
Remote Aws Data Engineer jobs near you

AWS Data Engineer

Qode

CO • On-site, Remote

$114K - $137K/yr

Full-time

Posted 6 days ago

Job description

Job Brief
As an AWS Data Engineer, your role will be to design, develop, and maintain scalable data pipelines on AWS. You will work closely with technical analysts, client stakeholders, data scientists, and other team members to ensure data quality and integrity while optimizing data storage solutions for performance and cost-efficiency. This role requires leveraging AWS native technologies and Databricks for data transformations and scalable data processing.
Responsibilities
• Lead and support the delivery of data platform modernization projects.
• Design and develop robust and scalable data pipelines leveraging AWS native services.
• Optimize ETL processes, ensuring efficient data transformation.
• Migrate workflows from on-premise to AWS cloud, ensuring data quality and consistency.
• Design automations and integrations to resolve data inconsistencies and quality issues
• Perform system testing and validation to ensure successful integration and functionality.
• Implement security and compliance controls in the cloud environment.
• Ensure data quality pre- and post-migration through validation checks and addressing issues regarding completeness, consistency, and accuracy of data sets.
• Collaborate with data architects and lead developers to identify and document manual data movement workflows and design automation strategies.
Skills and Requirements
• 10+ years' experience with a core data engineering skillset leveraging AWS native technologies (AWS Glue, Python, Snowflake, S3, Redshift).
• Experience in the design and development of robust and scalable data pipelines leveraging AWS native services.
• Proficiency in leveraging Snowflake for data transformations, optimization of ETL pipelines, and scalable data processing.
• Experience with streaming and batch data pipeline/engineering architectures.
• Familiarity with DataOps concepts and tooling for source control and setting up CI/CD pipelines on AWS.
• Hands-on experience with Databricks and a willingness to grow capabilities.
• Experience with data engineering and storage solutions (AWS Glue, EMR, Lambda, Redshift, S3).
• Strong problem-solving and analytical skills.
• Knowledge of Dataiku is needed
• Graduate/Post-Graduate degree in Computer Science or a related field.
• AWS S3 (data storage, export, recall)
• Athena (querying data lakes)
• Data pipelines (batch & near-real-time)
• Integration with external systems (FHIR)
• Secure data handling (KMS, Macie)
• Cloud-native analytics
• Multi-account, multi-region data architecture
• BI integrations: Power BI, Tableau, QuickSight

Apply