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Full Stack Data Engineer Jobs (NOW HIRING)

SOSi

Full Stack Data Engineer

Doral, FL · On-site

SOSi is seeking a Full-Stack Data Engineer to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances ...

Ford Motor Company

Full Stack Data Engineer

Dearborn, MI · On-site

$138K - $178K/yr

Full Stack Data Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned ...

rockITdata

Full Stack Data Engineer

Arlington, VA · Remote

We are seeking a talented and experienced Full Stack Data Engineer to join our team. The ideal candidate will have a strong background in both data engineering and software development, with ...

SysMind Tech

Data Engineer

Charlotte, NC · On-site

$111K - $134K/yr

We are seeking a highly skilled Full Stack Data Engineer to join our team. This role focuses on designing, developing, and supporting modern data solutions across a cloud-based data stack. The ideal ...

Boeing

Full Stack Data Scientist

Seattle, WA · Hybrid

The full stack data scientist in this role will partner closely with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders to ...

Boeing

Full Stack Data Scientist

Seattle, WA · Hybrid

The full stack data scientist in this role will partner closely with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders to ...

Boeing

Full Stack Data Scientist

Arlington, VA · Hybrid

The full stack data scientist in this role will partner closely with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders to ...

Boeing

Full Stack Data Scientist

Arlington, VA · Hybrid

The full stack data scientist in this role will partner closely with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders to ...

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All JobsFull Stack Data Engineer Jobs

Full Stack Data Engineer information

See salary details

$44.5K

$134.8K

$190.5K

How much do full stack data engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for full stack data engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior full stack data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries approaching or exceeding $500,000 annually, especially in high-cost living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires a combination of technical proficiency, leadership, and industry experience.

What is the difference between Full Stack Data Engineer vs Data Scientist?

AspectFull Stack Data EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science or related fields
Work EnvironmentBuild data pipelines, manage databases, develop APIsAnalyze data, create models, generate insights
Industry UsageTech, finance, healthcare, where data infrastructure is keyResearch, analytics, product development teams

Full Stack Data Engineers focus on building and maintaining data infrastructure, integrating data from various sources, and ensuring data availability. Data Scientists analyze data, develop models, and generate insights. While both roles require strong technical skills, Full Stack Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What does a full-stack data engineer do?

A full-stack data engineer designs, develops, and maintains data pipelines, databases, and data processing systems across both backend and frontend components. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis and application use. This role often requires knowledge of data architecture, ETL processes, and programming skills to support data-driven decision-making.

Can I make 200K as a data engineer?

Full Stack Data Engineers with extensive experience, advanced skills in cloud platforms, and expertise in tools like Spark or Hadoop can potentially earn salaries of $200,000 or more, especially in high-cost-of-living areas or senior roles. Salary levels depend on factors such as location, industry, company size, and individual qualifications.

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

To thrive as a Full Stack Data Engineer, you need strong expertise in data modeling, ETL processes, and proficiency in both backend (e.g., Python, Java) and frontend (e.g., JavaScript, React) development, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), big data tools (like Spark or Hadoop), and database systems (SQL and NoSQL) is typically required, and certifications in these technologies are advantageous. Excellent problem-solving, communication, and collaboration skills help you bridge gaps between data, development, and business teams. These skills ensure you can design, build, and maintain scalable data solutions that meet organizational needs efficiently.

What engineers make $300,000 a year?

Full Stack Data Engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $300,000 or more annually. High compensation often reflects seniority, specialized knowledge, and leadership roles within organizations. Certifications like AWS or Google Cloud and a strong portfolio can also contribute to higher salaries.

How does a Full Stack Data Engineer typically balance responsibilities between backend data infrastructure and frontend data presentation tasks?

Full Stack Data Engineers are often required to split their time between developing robust backend data pipelines and creating user-facing tools or dashboards that visualize data insights. This dual responsibility means you'll need to prioritize tasks based on project needs, effectively collaborating with data scientists, analysts, and frontend developers. Communication is key, as you'll bridge gaps between technical teams and business stakeholders, ensuring data flows seamlessly from source systems to end users. Over time, many engineers find opportunities to specialize further or move into leadership roles overseeing data architecture and team strategy.

What is a Full Stack Data Engineer?

A Full Stack Data Engineer is a professional who designs, builds, and maintains the entire data pipeline, from data collection and storage to processing and visualization. They work with both the backend infrastructure (such as databases, data warehouses, and ETL processes) and frontend tools (like dashboards or reporting systems) to ensure data is accessible and usable for analytics. Full Stack Data Engineers possess skills in programming, database management, data modeling, cloud platforms, and often data visualization, allowing them to manage every stage of data flow within an organization.
More about Full Stack Data Engineer jobs
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Full Stack Data Engineer jobs near you
Full Stack Data Engineer

Full Stack Data Engineer

SOSi

Doral, FL • On-site

Full-time

Re-posted 7 days ago

Job description

Company Description
Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Job Description
**This position is contingent upon contract award**
SOSi is seeking a Full-Stack Data Engineer to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.
Essential Job Duties:
  • Develop and maintain the data pipeline infrastructure, ensuring scalable ingestion, transformation, and integration of structured and unstructured datasets within the cloud-based CIP platform.
  • Optimize data storage strategies, implementing efficient query execution, indexing, and retrieval techniques for high-volume mission datasets.
  • Integrate APIs for secure data sharing across operational environments, ensuring controlled access and compliance with security frameworks.
  • Submit the Data Pipeline Optimization Report, detailing improvements in ingestion speed, storage efficiency, and API integrations.
  • Integrate all ingestion and transformation workflows with the Identity and Access Management (IAM) framework provisioned under other work orders; and coordinate with the work order team to define required roles, enforce RBAC policies, and maintain compliance with authentication and access standards across IL environments.

Qualifications
  • Active TS/SCI clearance.
  • Bachelor's degree in Computer Science, Data Engineering, or a related field, or five (5) years of equivalent experience in full-stack development and data engineering.
  • Knowledge and capability to develop, maintain, and optimize data integration pipelines, API services, and front-end interfaces for accessing and visualizing geospatial and structured data.
  • Proficient in Data Lakes platforms such as Databricks, Kubernetes, ESRI ArcGIS environments, and cloud-based data engineering.
  • Expertise in building scalable, secure web applications, implementing metadata-driven search and retrieval features, and integrating APIs for seamless data interoperability is required
  • Demonstrated experience in: Developing and deploying full-stack applications that enable data visualization, dashboarding, and analytics within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases. Implementing RESTful and GraphQL APIs for seamless data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources.
  • Managing CI/CD pipelines, containerized deployments in Kubernetes, and API authentication mechanisms to ensure secure access to research products.
  • Optimizing database queries and indexing strategies for large-scale geospatial and structured datasets.

Preferred Qualifications:
  • Desirable but not required certifications include AWS Certified Data Analytics - Specialty, Microsoft Certified: Azure Data Engineer Associate, or ESRI ArcGIS Developer Certification.

Additional Information
Work Environment
  • Normal office conditions.

Working at SOSi
All interested individuals will receive consideration and will not be discriminated against for any reason.

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