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Aws Data Scientist Jobs (NOW HIRING)

Qode

AWS Data Engineer

CO · On-site +1

$114K - $137K/yr

... AWS ... You will work closely with technical analysts, client stakeholders, data scientists, and other team ...

Random Bit

AWS Data Architect

Atlanta, GA · Remote

$130K - $165K/yr

AWS Data Architect/Engineer Company Overview Random Bit is a system modernization partner that ... Bachelor's degree in information management, data science, statistics, public health, health ...

Random Bit

AWS Data Architect

Atlanta, GA · On-site +1

$130K - $165K/yr

AWS Data Architect/Engineer Company Overview Random Bit is a system modernization partner that ... Bachelor's degree in information management, data science, statistics, public health, health ...

Sarian, Inc.

AWS Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Role: AWS Data Engineer Location: Seattle, WA Onsite position Fulltime position *****NO Corp to ... Work closely with data scientists, analysts, and business stakeholders to understand data needs and ...

Incedo Inc

AWS Data Architect

Fort Mill, SC · On-site

$56 - $72/hr

... and Life Sciences drive business outcomes through Data, AI, Engineering, and Operations excellence. Role Summary We are looking for a hands-on AWS Data Architect to design, build, and scale ...

New

Princeton IT Services

AWS Data Architect

Neenah, WI · On-site

$64.50 - $82.75/hr

AWS Data Architect Location: Neenah, WI Job type: Contract Position Overview We are seeking a ... Bachelor's or Master's degree in Computer Science, Information Systems, or a related field * 7+ ...

Cloud BC Labs

AWS Data Engineer

Alameda, CA · On-site

$129K - $155K/yr

BE / MCA / Any Master degree in Computer Science Primary (Must have skills)* Experience: Minimum of 8 years of experience in data engineering with a focus on AWS data services. Skills: Proficiency in ...

Arkhya Tech

Lead AWS Data Engineer

Newark, NJ · On-site

$119K - $143K/yr

Lead AWS Data Engineer Location: Newark, NJ (Hybrid) Domain: Banking or Insurance Job Summary: We ... This role will collaborate closely with data scientists, analysts, and other business stakeholders ...

Diverse Lynx

AWS Cloud Data Lake Lead

Cambridge, VT · On-site

The role involves defining data science operations strategy, architecting scalable ML pipelines, and overseeing AWS Data Lake architectures. Responsibilities : • Lead and manage a team of 6 data ...

BTree Solutions, Inc.

SR. AWS DATA ENGINEER

Reston, VA · On-site

$119K - $143K/yr

Job Title: SR. AWS DATA ENGINEER Location: Reston, VA Duration: 12+ Months Visa: USC, GC, H1B and ... Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Ztek Consulting INC

Data Scientist

Charlotte, NC · On-site

Utilize AWS analytics services Athena Redshift QuickSight EMR for advanced reporting and visualization * Work with stakeholders to translate business objectives into data science solutions and ...

THOMSON REUTERS

Data Scientist

Mclean, VA · On-site

As a Data Scientist, you will be responsible for selecting, developing, fine-tuning, evaluating ... Familiarity with AWS, data pipelines, and data engineering practices * Hands-on experience with ...

Capgemini

AWS Data Engineer

New York, NY · On-site

$125K - $150K/yr

... Science, Engineering, or related field 8+ years of experience in data engineering or related roles Strong hands-on experience with AWS services, including: o Amazon S3 o AWS Glue o Amazon Redshift ...

United Airlines

AWS Data Engineer

Manhattan, NY

$126K - $151K/yr

... Science, Engineering, or related field 8+ years of experience in data engineering or related roles Strong hands-on experience with AWS services, including: o Amazon S3 o AWS Glue o Amazon Redshift ...

VTG

Data Scientist

Beavercreek, OH · On-site

The Data Scientist will design, prototype, and implement a data management and application ... Cloud development experience, preferably in AWS * Excellent verbal and written communication skills

CYNET SYSTEMS

Data Scientist

Charlotte, NC · On-site

$60 - $65/hr

Utilize AWS analytics services (Athena, Redshift, QuickSight, EMR) for advanced reporting and visualization. * Work with stakeholders to translate business objectives into data science solutions and ...

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Aws Data Scientist information

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How much do aws data scientist jobs pay per year?

As of Aug 20, 2026, the average yearly pay for aws data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is an AWS data scientist?

An AWS Data Scientist leverages Amazon Web Services (AWS) cloud tools to analyze large datasets, build machine learning models, and derive insights for business decisions. They work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to clean, process, and visualize data efficiently. Their role involves data engineering, statistical analysis, and deploying scalable machine learning solutions in the cloud. AWS Data Scientists collaborate with engineers and analysts to optimize data workflows and improve predictive analytics.

What types of projects and collaborations can I expect as an AWS data scientist?

As an AWS Data Scientist, you will frequently work on projects involving large-scale data processing, predictive modeling, and developing machine learning pipelines using AWS cloud platforms. Collaboration is key, as you'll interact regularly with data engineers, software developers, business analysts, and sometimes non-technical stakeholders to understand requirements and deliver data-driven solutions. Many roles offer opportunities to lead innovations, contribute to cloud architecture decisions, and upskill in emerging AWS technologies. You'll gain practical experience with real-world datasets and help drive impactful decisions across multiple departments. This collaborative, dynamic environment often presents excellent opportunities for career growth and specialization within both data science and cloud computing realms.

What are the key skills and qualifications needed to thrive in the AWS data scientist position, and why are they important?

To thrive as an AWS Data Scientist, you need strong statistical analysis, machine learning expertise, and proficiency in programming languages like Python or R, often with a degree in computer science or a related field. Familiarity with AWS services such as Sagemaker, Redshift, and Athena, as well as certifications like AWS Certified Machine Learning – Specialty, are highly valued. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate data insights into actionable business solutions. These competencies ensure efficient development, deployment, and scaling of data-driven models in cloud-based environments.

Does AWS hire data scientists?

Yes, AWS hires data scientists to work on machine learning, data analysis, and cloud-based AI solutions. These roles often require skills in programming, statistical analysis, and familiarity with AWS services like SageMaker. Opportunities are available across various teams and locations, with roles typically requiring relevant experience and technical certifications.
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Aws Data Scientist jobs near you
Infographic showing various Aws Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

AWS Data Engineer

Qode

CO • On-site, Remote

$114K - $137K/yr

Full-time

Re-posted 22 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

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