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Amazon Data Science Jobs in Kentucky (NOW HIRING)

$78K - $106K/yr

... Science, Engineering, or a related field. * 3+ years of experience working with PySpark and SQL. * 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue. * 2+ ...

$113K - $188K/yr

... data science, from data querying and wrangling to data engineering, to data visualization ... Experience with approved enterprise AI tools (e.g., Amazon Q, Azure OpenAI, Microsoft Copilot ...

$14.25 - $18.50/hr

... Amazon CodeWhisperer, Quickbase, Airtable Cobuilder, Databutton, AutoNav, ExoMiner, MLNav, ASPEN ... Staying up to date on the latest AI developments with an understanding of data science.

Amazon in North America is one of the most competitive, fastest-moving, and most data-rich ... Data Analytics & Science * Lead the analytics and data science function supporting the business ...

... Azure and Amazon Web Services (AWS) environments, establishing standards, patterns, and best ... Bachelor's degree in Computer Science, Data Science, Software Engineering, Systems Engineering ...

... Azure and Amazon Web Services (AWS) environments, establishing standards, patterns, and best ... Bachelor's degree in Computer Science, Data Science, Software Engineering, Systems Engineering ...

Master's Degree in Computer Science, Information Security, Engineering, Data Science or related ... Amazon Web Services (AWS), Google Cloud Platform (GCP) and/or Microsoft Azure cloud computing ...

$145K - $196K/yr

... limits, data access, and safety constraints. Maintain prompt/schema versioning and document ... Science, or a related field and... #J-18808-Ljbffr

Master's Degree in Computer Science, Information Security, Engineering, Data Science or related ... Amazon Web Services (AWS), Google Cloud Platform (GCP) and/or Microsoft Azure cloud computing ...

$85K - $141K/yr

... data science, from data querying and wrangling to data engineering, to data visualization ... Experience with approved enterprise AI tools (e.g., Amazon Q, Azure OpenAI, Microsoft Copilot ...

$61K - $122K/yr

Descritivo de Cargo Sales Analyst, Amazon About Abbott Our nutrition business develops science ... Address and resolve data integrity, integration and system issues. * Identify and respond to ...

$90K - $119K/yr

... Amazon Bedrock, and Google Vertex AI. * Proficiency in TypeScript and familiarity with key ... Exposure toadjacent skillsets such asdata engineering, data science, UI/UX, cloud engineering, and ...

$135K - $155K/yr

... Science, or related field * Creative thinker who is intellectually curious, with a passion for ... Amazon Relational Database Service (Aurora, MySQL) * Microsoft SQL Server * Snowflake * Exceptional ...

... data mining, parallel and distributed computing, high-performance computing * Preferred Qualifications:- PhD in computer science, computer engineering, or related field Amazon is an equal opportunity ...

New

Bachelors in Technology or Engineering (CS, EE, Robotics, Data Science, Physics, Mathematics, etc ... Background in building solutions on Amazon AWS, Google Cloud Services, Microsoft Azure is a plus.

Showing results 41-60

Amazon Data Science information

See Kentucky salary details

$40K

$143.3K

$211.5K

How much do amazon data science jobs pay per year?

As of Sep 11, 2026, the average yearly pay for amazon data science in Kentucky is $143,323.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,900.00 and $147,600.00 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 Kentucky?

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

Infographic showing various Amazon Data Science job openings in Kentucky as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 9% Part Time, 7% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $143,323 per year, or $68.9 per hour.

AWS Data Engineer (Senior)

On-site

$78K - $106K/yr

Other

Posted 9 days ago


Key responsibilities

  • Build and maintain data pipelines on Amazon EMR or Amazon Glue that run in production.

  • Design data models and end-user querying on Amazon Redshift or Snowflake, Amazon Athena, and Presto.

  • Build and maintain pipeline orchestration with Airflow.


Job description

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.

This is a senior role in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters, at meaningfully lower engagement cost than traditional data consulting. Customers come to us after a data program has stalled pipelines nobody trusts, warehouses nobody runs new workloads on, a modernization that produced diagrams instead of production systems.

Aedeon handles automated source discovery, schema mapping, lineage extraction, and parallel-run validation. You own what agents can't: target architecture, data model decisions, pipeline design under real constraints, and the calls that make a cutover safe. You'll build with PySpark and SQL on EMR and Glue, model for Redshift, Snowflake, Athena, and Presto, orchestrate with Airflow and your work will reach production, not a slide deck.

What you will do?
  • Build and maintain data pipelines on Amazon EMR or Amazon Glue that run in production.
  • Design data models and end-user querying on Amazon Redshift or Snowflake, Amazon Athena, and Presto.
  • Build and maintain pipeline orchestration with Airflow.
  • Work with customer and internal teams to understand data needs and design the solutions that meet them.
  • Troubleshoot and optimize pipelines and data models until they hold up under real load.
  • Write and maintain PySpark and SQL scripts to extract, transform, and load data.
  • Document and communicate technical decisions to technical and non-technical audiences — customers sign off on what we ship.
  • Track new AWS data technologies and judge their impact on the systems we run.
What are we looking for?
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience working with PySpark and SQL.
  • 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue.
  • 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto.
  • 1+ years of experience building and maintaining pipeline orchestration using Airflow.
  • Strong problem-solving and troubleshooting skills.
  • Excellent communication and collaboration skills.
  • Ability to work independently and within a team environment.
You are preferred if you have
  • AWS Data Analytics Specialty Certification
  • Experience with Agile development methodology
How we work?

We run a forward-deployed model. Senior engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally fixed dates, with Mactores absorbing overage cost for delays inside our control. Aedeon absorbs scale; you absorb judgment. That means less of your week goes to inventory spreadsheets and manual validation, and more goes to architecture, data modeling, and cutover strategy. The culture is casual and steers clear of rigid corporate habits. We measure ourselves by what ships.

Compensation Additional Information

Life at Mactores

We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.

1. Be one step ahead

2. Deliver the best

3. Be bold

4. Pay attention to the detail

5. Enjoy the challenge

6. Be curious and take action

7. Take leadership

8. Own it

9. Deliver value

10. Be collaborative

We would like you to read more details about the work culture on https://mactores.com/careers

The Path to Joining the Mactores Team

At Mactores, our recruitment process is structured around three distinct stages:

Pre-Employment Assessment:

A series of evaluations of your technical proficiency and suitability for the role.

Managerial Interview: The hiring manager engages with you in multiple discussions, 30 minutes to an hour each, covering technical skills, hands-on experience, leadership potential, and communication.

HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.

Mactores provides equal opportunities in all employment practices. We don't discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This applies to every part of the employment relationship, recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs.

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