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Amazon Data Science Jobs in Illinois (NOW HIRING)

Data Engineer

Dahlgren, IL Β· On-site

$110K - $132K/yr

At least one year of experience supporting data science applications and analytical tools such as Python, Jupyter, Amazon SageMaker Studio, AWS Glue DataBrew, or Amazon QuickSight. * Experience ...

Advanced Python experience for data science, machine learning, model experimentation, automation ... AWS cloud experience, including familiarity with services such as Amazon SageMaker, Amazon Bedrock ...

Advanced Python experience for data science, machine learning, model experimentation, automation ... AWS cloud experience, including familiarity with services such as Amazon SageMaker, Amazon Bedrock ...

Strong Python experience for data science, machine learning, model experimentation, automation, API ... AWS cloud experience, including familiarity with services such as Amazon SageMaker, Amazon Bedrock ...

Strong Python experience for data science, machine learning, model experimentation, automation, API ... AWS cloud experience, including familiarity with services such as Amazon SageMaker, Amazon Bedrock ...

Senior Data Engineer

Chicago, IL Β· On-site

$109K - $148K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Design, develop, and deploy end-to-end data pipelines on AWS using services such as Amazon S3, AWS ...

Senior Data Engineer

Chicago, IL Β· On-site

$109K - $148K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Design, develop, and deploy end-to-end data pipelines on AWS using services such as Amazon S3, AWS ...

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Showing results 1-20

Amazon Data Science information

See Illinois salary details

$44.6K

$159.9K

$236K

How much do amazon data science jobs pay per year?

As of Sep 11, 2026, the average yearly pay for amazon data science in Illinois is $159,907.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,400.00 and $164,700.00 per year, depending on experience, location, and employer.

What is an Amazon data science?

An Amazon Data Science job involves leveraging data to drive business decisions, optimize operations, and enhance customer experiences. Data scientists at Amazon work with machine learning, statistical modeling, and big data technologies to analyze vast datasets and generate actionable insights. They collaborate with engineering, product, and business teams to develop data-driven solutions for challenges such as recommendation systems, demand forecasting, and fraud detection. Strong programming skills in Python or Scala, expertise in SQL, and experience with AWS tools are commonly required.

What types of projects and challenges can I expect as an Amazon data science team member?

As an Amazon Data Science team member, you can expect to work on projects ranging from optimizing supply chains and recommendation systems to improving customer experiences and forecasting demand. Daily responsibilities often involve analyzing large data sets, building predictive models, and collaborating closely with product managers, software engineers, and business leaders. The pace is fast, with opportunities to tackle complex problems that have a direct impact on Amazon’s customers and operations. You’ll also have the chance to grow your skills through cross-team projects, participation in internal workshops, and exposure to emerging data science technologies.

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

To thrive as an Amazon Data Science professional, you need strong analytical abilities, expertise in statistics and machine learning, and a solid educational background in computer science, mathematics, or a related field. Proficiency in programming languages such as Python or R, familiarity with big data tools like AWS, Spark, or Hadoop, and relevant certifications (e.g., AWS Certified Data Analytics) are often required. Effective communication, business acumen, and collaborative problem-solving set exceptional candidates apart. These skills are crucial for transforming complex data into actionable insights that drive impactful business decisions at Amazon.

Does Amazon have data science jobs?

Yes, Amazon offers data science jobs across various teams, focusing on areas such as machine learning, data analysis, and predictive modeling. These roles typically require skills in programming, statistics, and tools like Python, R, or SQL, and often involve working in collaborative, fast-paced environments. Candidates should review Amazon's careers page for current openings and specific role requirements.

What are the most commonly searched types of Amazon Data Science jobs in Illinois?

The most popular types of Amazon Data Science jobs in Illinois are:

What job categories do people searching Amazon Data Science jobs in Illinois look for?

The top searched job categories for Amazon Data Science jobs in Illinois are:

Infographic showing various Amazon Data Science job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $159,907 per year, or $76.9 per hour.

Data Engineer

Dahlgren, IL β€’ On-site

Delaware Nation Industries
501 - 1,000 employees

$110K - $132K/yr

Other

Posted 17 days ago


Key responsibilities

  • Design, build, troubleshoot, and tune cloud-native data engineering solutions using AWS platform and software services.

  • Develop and administer data ingestion, ETL, integration, transformation, validation, publication, and lifecycle-management workflows.

  • Create REST APIs and web services to expose data to JWAC-developed applications and analytical systems.


Job description

DNI is seeking a highly qualified Data Engineer to support the Joint Warfare Analysis Center (JWAC) under Air Force JWAC IT Services (JITS) Task Order 2. The Data Engineer will design, implement, secure, monitor, and optimize cloud-native data engineering solutions that support data science, artificial intelligence/machine learning (AI/ML), agentic services, hosted models, and large language model (LLM) optimization. The role integrates data engineering, FinOps, Zero Trust security, and AI/ML infrastructure responsibilities within a single position.

This position is expected to work onsite at JWAC in Dahlgren, Virginia, supporting a TS/SCI/SAP environment.

Responsibilities
  • Design, build, troubleshoot, and tune end-to-end cloud-native data engineering solutions using AWS platform and software services.
  • Develop and administer data ingestion, ETL, integration, transformation, validation, publication, and lifecycle-management workflows.
  • Integrate structured and unstructured data from databases, web services, message traffic, data dumps, documents, and other sources.
  • Design data architectures and managed data stores that support analytics, feature engineering, model training, and real-time inference.
  • Develop solutions using AWS services such as AWS Glue, Amazon Athena, Amazon Redshift, Amazon Kinesis, AWS Lake Formation, AWS Glue Data Catalog, Amazon RDS, Amazon Aurora, and Amazon DynamoDB.
  • Create REST APIs and web services to expose data to JWAC-developed applications and analytical systems.
  • Support AI/ML infrastructure, including model hosting, model-ready datasets, agentic workflow orchestration, retrieval-augmented generation (RAG), and LLM integration and optimization.
  • Develop automation, monitoring, alerting, and self-healing capabilities using AWS-native tools such as Amazon CloudWatch and AWS CloudTrail.
  • Implement data discovery and search capabilities using services such as Amazon OpenSearch Service, AWS Glue Data Catalog, and Amazon Kendra.
  • Apply FinOps practices, including resource tagging, cost allocation, right-sizing, storage tiering, query optimization, budget monitoring, cost-per-workload analysis, and AI/LLM cost tracking.
  • Implement DoD Zero Trust and NIST SP 800-53 Rev. 5 security controls across data engineering and AI service environments.
  • Configure identity and access management, least-privilege access, encryption at rest and in transit, network segmentation, certificate management, and security monitoring.
  • Support security assessments, compliance documentation, data-flow diagrams, control mappings, and authorization activities.
  • Gather requirements, evaluate data sources, communicate technical recommendations, and document architecture, processes, costs, risks, and implementation decisions.
  • Develop briefings, technical proposals, operating procedures, user documentation, training materials, and knowledge-transfer products.
  • Collaborate with Government stakeholders, data scientists, analysts, cybersecurity personnel, cloud engineers, and other technical teams.
  • Bachelor of Science degree in computer science, computer engineering, data engineering, data science, or a related technical discipline.
  • At least three years of full-time experience in computer science, data engineering, or data science, including hands-on software development lifecycle experience.
  • Recent experience designing or implementing data engineering solutions or cloud-native systems on AWS.
  • At least one year of experience with cloud-native data warehouse or analytics platforms, such as Amazon Redshift, Amazon Athena, AWS Glue Data Catalog, or AWS Lake Formation.
  • At least one year of experience supporting data science applications and analytical tools such as Python, Jupyter, Amazon SageMaker Studio, AWS Glue DataBrew, or Amazon QuickSight.
  • Experience preparing data for data scientists, including data preparation, feature engineering, and model-ready dataset construction.
  • At least one year of experience implementing cloud-native data security controls, including IAM, encryption, and network segmentation.
  • Ability to meet DoD 8140.03 requirements for the applicable work roles, including Primary Work Role 422 – Data Architect (Intermediate).
  • Ability to obtain and maintain the required TS/SCI/SAP access.
  • Ability to work onsite in Dahlgren, Virginia, during established core hours and support scheduled maintenance activities as required.
Preferred Qualifications
  • Experience with Amazon Bedrock, Knowledge Bases, RAG architectures, agentic services, or LLM prompt and token optimization.
  • Experience with AWS Security Hub, Amazon GuardDuty, AWS KMS, AWS IAM Identity Center, and AWS Certificate Manager.
  • Experience applying NIST SP 800-53 Rev. 5 and DoD Zero Trust Architecture principles.
  • Experience with FinOps dashboards and tools such as AWS Cost Explorer, AWS Budgets, and AWS Cost and Usage Reports.
  • Experience with data discovery, federated search, geospatial or non-geospatial search, and knowledge-management solutions.
  • Experience supporting classified or highly regulated Department of Defense environments.
  • AWS certifications, data engineering certifications, or relevant DoD cybersecurity certifications.
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