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Remote Amazon Data Engineer Jobs in Houma, LA (NOW HIRING)

ABB

Strategic Segment Proposal Engineer

LA · Remote

... data centers and critical manufacturing facilities). You will work with Strategic Account Sales ... This is a remote position. Candidates can be located anywhere in the US. This role is contributing ...

All JobsAmazon Data Engineer JobsRemote Amazon Data Engineer JobsRemote Amazon Data Engineer Jobs in Houma, LA

Remote Amazon Data Engineer information

See Houma, LA salary details

$43K

$125.4K

$171.6K

How much do remote amazon data engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote amazon data engineer in Houma, LA is $125,407.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,700.00 and $132,900.00 per year, depending on experience, location, and employer.

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 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 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.

Can I work remotely as a remote amazon data engineer?

Yes, many Amazon Data Engineer roles are available as remote positions, allowing professionals to work from home or other locations. These roles typically require strong skills in data pipelines, cloud platforms like AWS, and relevant certifications, with companies often providing remote work options depending on the team and project needs.

How much do remote Amazon data engineers make?

Remote Amazon data engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and skill set. Salaries can vary based on factors such as certifications, expertise in tools like AWS and Spark, and the level of seniority in the role.

What cities near Houma, LA are hiring for Remote Amazon Data Engineer jobs?

Cities near Houma, LA with the most Remote Amazon Data Engineer job openings:

Remote Amazon Data Engineer jobs near you
Infographic showing various Remote Amazon Data Engineer job openings in Houma, LA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $125,407 per year, or $60.3 per hour.

Senior Manager Data Science & AI

Bollinger Shipyards

Raceland, LA • Remote

Full-time

Re-posted 19 days ago

Bollinger Shipyards rating

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Job Title: Senior Manager Data Science & AI

Location: Remote USA

Position Overview: The Senior Manager, Data Science & AI is responsible for establishing and scaling enterprise artificial intelligence, machine learning, and advanced analytics capabilities across Bollinger Shipyards. This role leads the identification, prioritization, development, and operationalization of AI solutions that improve forecasting, bidding, operational efficiency, planning, and decision-making.

The role partners closely with business leaders, Data Engineering, Analytics, and Enterprise Architecture to ensure AI initiatives are aligned to strategic priorities and successfully integrated into enterprise operations.

Key Responsibilities:

  • ·         Define and execute the enterprise roadmap for AI, machine learning, and advanced analytics initiatives
  • ·         Identify and prioritize high-value AI and predictive analytics use cases aligned to operational and strategic objectives
  • ·         Lead development of models supporting forecasting, cost estimation, scheduling, bidding optimization, operational efficiency, and intelligent automation
  • ·         Establish standards and governance for model development, validation, deployment, monitoring, and lifecycle management
  • ·         Ensure AI and ML solutions are integrated into enterprise workflows and production systems
  • ·         Partner with Data Engineering teams to ensure availability of scalable, high-quality datasets for model development
  • ·         Collaborate with business leaders to drive adoption and measurable business value from AI capabilities
  • ·         Evaluate emerging AI technologies, platforms, and opportunities relevant to Bollinger’s operational environment
  • ·         Lead and develop data science and ML engineering resources
  • ·         Ensure responsible, secure, and compliant use of AI technologies and enterprise data
  • ·         Establish KPIs and performance measures for AI initiatives and operational impact

Qualifications:

•           Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or related field

•           8+ years of experience in data science, AI, machine learning, or advanced analytics roles

•           3+ years of leadership experience

•           Proven experience leading enterprise AI and ML initiatives from concept through operational deployment

•           Strong background in statistical modeling, machine learning, predictive analytics, and optimization techniques

•           Experience working with large and complex enterprise datasets

•           Experience leading technical teams and enterprise-scale initiatives

Skills and Abilities:

•           Experience in manufacturing, industrial, shipbuilding, engineering, or operational environments

•           Experience with Azure AI, ML Ops, cloud AI platforms, and modern AI frameworks

•           Familiarity with Generative AI, intelligent automation, and agent-based AI applications

•           Experience operationalizing AI solutions within ERP or operational systems

•           Knowledge of AI governance, model risk management, and responsible AI practices

Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.

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