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Remote Amazon Data Engineer Jobs in Arizona (NOW HIRING)

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... In partnership with engineering teams, you will design and deliver scalable solutions that support ...

DevOps Engineer

Tucson, AZ · On-site +1

$50 - $65/hr

Tucson, Arizona (Remote) Employment Type: Contract Role Overview We are seeking a DevOps Engineer with a primary focus on data engineering and BI development within an AWS environment. This role is ...

You will have the flexibility to work fully remote from anywhere across Arizona. Insight at a ... At least 5 years specifically focused on Data Engineering, Analytics, or Machine Learning. * Cloud ...

GCP Engineer

Tempe, AZ · On-site +1

... and/or remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a GCP Engineer on the AI & Data team, you will be responsible for... * Build, configure, and ...

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Showing results 1-20

Remote Amazon Data Engineer information

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

To thrive as a Remote Amazon Data Engineer, you need strong expertise in data modeling, ETL development, SQL, and programming languages such as Python or Java, typically supported by a degree in computer science or a related field. Familiarity with AWS services like Redshift, S3, Glue, and data pipeline tools, as well as certifications such as AWS Certified Data Analytics, are highly valued. Excellent problem-solving, communication, and self-management skills help remote engineers collaborate effectively and deliver reliable data solutions. These abilities are crucial for ensuring robust, scalable data infrastructure and supporting data-driven decision-making in a distributed work environment.

What are some common challenges faced by Remote Amazon Data Engineers, and how can they be addressed?

Remote Amazon Data Engineers often encounter challenges related to collaborating across time zones and ensuring clear communication with global teams. Effective use of collaboration tools, regular virtual meetings, and clear documentation can help bridge these gaps. Additionally, managing large-scale data pipelines on AWS requires staying updated on best practices for security, scalability, and cost optimization. Proactively participating in team stand-ups and engaging in continuous learning about AWS services can significantly enhance productivity and project outcomes.

What does a Remote Amazon Data Engineer do?

A Remote Amazon Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and databases for Amazon or companies using Amazon Web Services (AWS). They work remotely to process large volumes of data, ensure data quality, and enable efficient data analysis. Their tasks typically include extracting data from various sources, transforming it into usable formats, and loading it into data warehouses or analytics platforms. They often use AWS tools such as Redshift, Glue, S3, and Lambda to manage infrastructure and automate workflows. Strong programming skills in languages like Python or SQL are essential for this role.

What is the difference between Remote Amazon Data Engineer vs Remote Amazon Data Analyst?

AspectRemote Amazon Data EngineerRemote Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDesigning data pipelines, managing ETL processesInterpreting data, creating reports and dashboards
Employer & Industry UsageTech companies, e-commerce, cloud servicesRetail, marketing, e-commerce
Common Search & ComparisonFocus on data infrastructure and pipelinesFocus on data insights and reporting

The main difference between a Remote Amazon Data Engineer and a Remote Amazon Data Analyst lies in their roles. Data Engineers build and maintain data pipelines and infrastructure, requiring technical skills in data architecture. Data Analysts interpret data to generate insights, focusing on analysis and reporting. Both roles are essential in data-driven companies but serve different functions within the data ecosystem.

What are the most commonly searched types of Amazon Data Engineer jobs in Arizona? The most popular types of Amazon Data Engineer jobs in Arizona are:
What are popular job titles related to Remote Amazon Data Engineer jobs in Arizona? For Remote Amazon Data Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Amazon Data Engineer jobs in Arizona look for? The top searched job categories for Remote Amazon Data Engineer jobs in Arizona are:
What cities in Arizona are hiring for Remote Amazon Data Engineer jobs? Cities in Arizona with the most Remote Amazon Data Engineer job openings:
Data Scientist I

Data Scientist I

USAA

Phoenix, AZ • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


USAA rating

8.2

Company rating: 8.2 out of 10

Based on 250 frontline employees who took The Breakroom Quiz

37th of 141 rated banks


Job description

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful.

We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs.

The Opportunity

As a Data Scientist, you will translate complex business challenges into practical, data-driven solutions using statistical analysis, machine learning, simulation, and optimization techniques. Your work will drive meaningful business impact by enabling automation, uncovering revenue opportunities, and reducing risk and operational costs. In partnership with engineering teams, you will design and deliver scalable solutions that support internal decision-making and power customer-facing applications. You will leverage your expertise in databases, cloud platforms, and programming to develop advanced analytical models, while collaborating with peers to enhance internal tools and expand the organization's library of data science capabilities.

Success in this role requires a strong technical foundation and domain expertise within banking and financial services, including an understanding of business processes and risk management practices. You will work across modern data and cloud ecosystems, utilizing tools such as AWS (Redshift, Glue, S3, Lambda), PySpark, and ETL technologies like DataStage and Informatica. Proficiency in Python visualization libraries (Matplotlib, Seaborn, iPython), Git for CI/CD automation, and workflow orchestration tools like Apache Airflow and BMC Control-M is essential. Additionally, experience with data engineering, cloud architecture, and Agile methodologies will support your ability to build, deploy, and maintain reliable models, working closely with model risk management to ensure accuracy and stability before production deployment.

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL.

Relocation assistance is not available for this position.

What you'll do:

  • Gathers, interprets, and manipulates structured and unstructured data to enable advanced analytical solutions for the business.
  • Develops scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.
  • Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
  • Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
  • Composes technical documents for knowledge persistence, risk management, and technical review audiences.
  • Assesses business needs to propose/recommend analytical and modeling projects to add business value.
  • Participates in the prioritization of analytics and modeling problems/research efforts with business and analytics leaders.
  • Contributes to the development of a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.
  • Translates business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.
  • Works closely with Data Engineering, IT, the business, and other internal stakeholders to deploy production-ready analytical assets that are aligned with the customer's vision and specifications while being consistent with modeling best practices and model risk management standards.
  • Maintains awareness of cutting-edge techniques.
  • Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
  • Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

What you have:

  • Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.


Experiences that will support your success:

  • 4 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 2 years of experience in predictive analytics or data analysis.
  • 2 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
  • 2 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
  • Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
  • Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
  • Experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
  • Experience in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • Ability to assess regulatory implications and expectations of distinct modeling efforts.
  • Experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.
  • Experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
  • Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.

What sets you apart:

  • US military experience through military service or a military spouse/domestic partner
  • Strong technical foundation with domain expertise in banking and financial services, including knowledge of business processes and risk management practices
  • Experience working across modern data and cloud ecosystems, including AWS services (Redshift, Glue, S3, Lambda) and PySpark
  • Hands-on experience with ETL tools such as DataStage and Informatica
  • Proficiency in Python visualization libraries (Matplotlib, Seaborn, iPython)
  • Experience with Git and CI/CD automation practices
  • Familiarity with workflow orchestration tools like Apache Airflow and BMC Control-M
  • Knowledge of data engineering principles and cloud architecture
  • Experience working in Agile environments and methodologies
  • Ability to build, deploy, and maintain reliable models, partnering with model risk management to ensure accuracy and stability before production deployment

Compensation range: The salary range for this position is: $114,080 - $218,030.

USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.).

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


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