We are seeking a Senior AWS Data Engineer to design and build cloud-native data platforms supporting scientific research at the NOAA. This role focuses on developing scalable AWS-based data pipelines, API-driven data platforms, and machine learning workflows that enable researchers to ingest, process, analyze, and visualize complex scientific and geospatial datasets.

You will work within an Agile development team to architect and implement secure, scalable data solutions used by research laboratories and programs across the country.

This is a hands-on engineering role focused on building production-ready cloud data systems in AWS.

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What You’ll Do

• Design and build AWS-based data pipelines for ingesting and processing large scientific datasets

• Develop API-driven data platforms to host and distribute datasets internally and externally

• Build and support machine learning pipelines for research and analytics workloads

• Architect scalable data lakes and cloud-native data platforms in AWS

• Implement infrastructure using Infrastructure as Code (Terraform preferred)

• Work with researchers and data scientists to support scientific and geospatial data workflows

• Develop architecture diagrams, technical documentation, and deployment plans

• Collaborate with cloud engineers, security teams, and program stakeholders in an Agile environment

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Required Experience

• 4–8 years of experience building data platforms, data pipelines, or cloud data infrastructure

• Hands-on experience with AWS data services

• Experience building end-to-end data pipelines and analytics platforms

• Experience developing API-driven data platforms

• Experience with Infrastructure as Code (Terraform or CloudFormation)

• Strong experience with Python or similar data engineering languages

• Experience working in cloud environments supporting analytics or machine learning

• Ability to work with both technical and non-technical stakeholders

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Nice to Have

• Experience working with scientific, research, or geospatial datasets

• Experience supporting federal or government environments

• Experience with machine learning workflows

• AWS certifications such as Solutions Architect or Data Specialty

• Experience with serverless data processing (Lambda, event-driven pipelines)

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Location

Remote (U.S.)

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Security

Ability to obtain a security clearance.

GAMA-1 also offers a variety of benefits, including health insurance coverage, life and disability insurance, 401(k) savings plan, training and career development opportunities, paid holidays and paid time off (PTO - to cover vacation, illness or disability, appointments, emergencies or other situations that require time off from work). For more information click here.

ABOUT GAMA-1

GAMA-1 is a rapidly growing technology business that is based in Greenbelt, Maryland. GAMA-1 Technologies provides strategic information assurance, information security, and business enterprise and networking solutions to the Federal Government. Our success is based on the utilization of industry and agency standards, establishment of standardized processes, and IT Services expertise. At GAMA-1, we believe employees should grow, achieve, and develop just as the company grows, achieves, and develops. GAMA-1 is committed to providing our employees with opportunities for career advancement throughout their employment. For more information, visit www.gama1tech.com

GAMA-1 is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to: veteran status, uniformed servicemember status, race, color, religion, sex, sexual orientation, gender identity, age, pregnancy (including childbirth, lactation and related medical conditions), national origin or ancestry, citizenship or immigration status, physical or mental disability, genetic information (including testing and characteristics), domestic violence victims, political orientation, status as a smoker or tobacco user, hairstyle, use of a service animal, education status, familial status, HIV/AIDS status, height, weight, reproductive healthcare decisions or any other category protected by federal, state or local law.