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Full Stack Data Engineer Jobs in Dallas, TX (NOW HIRING)

Wondr Health

Full-Stack Engineer

Dallas, TX · On-site +1

$145K - $160K/yr

Full-Stack Engineer REPORTS TO: Director, Software Engineering SUPERVISES: None JOB CLASS: Exempt PURPOSE: We're looking for a Full-Stack Engineer to join our product engineering team. You'll work ...

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All JobsFull Stack Data Engineer JobsFull Stack Data Engineer Jobs in Dallas, TX

Full Stack Data Engineer information

See Dallas, TX salary details

$44.2K

$133.9K

$189.3K

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

As of Aug 17, 2026, the average yearly pay for full stack data engineer in Dallas, TX is $133,887.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,300.00 and $157,000.00 per year, depending on experience, location, and employer.

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.

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 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 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 are popular job titles related to Full Stack Data Engineer jobs in Dallas, TX?

For Full Stack Data Engineer jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Full Stack Data Engineer jobs in Dallas, TX look for?

The top searched job categories for Full Stack Data Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Full Stack Data Engineer jobs?

Cities near Dallas, TX with the most Full Stack Data Engineer job openings:

Full Stack Data Engineer jobs near you
Infographic showing various Full Stack Data Engineer job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $133,887 per year, or $64.4 per hour.

Full Stack Software Engineer

Techvilla Solutions

Wilmer, TX • On-site

Full-time

Posted 11 days ago

Job description

We are seeking an experienced Senior Full Stack .NET Developer to design, develop, and maintain scalable cloud-based applications and integration services. The ideal candidate will have strong expertise in C#/.NET, React, SQL, and modern cloud technologies, with experience building APIs, event-driven architectures, and enterprise-grade applications. You will collaborate with cross-functional teams to deliver secure, high-quality software following Agile and DevOps best practices.

Core Responsibilities
  • Design, develop, and maintain full-stack web applications using C#/.NET and React.
  • Build and enhance RESTful APIs, middleware, and service-based integrations.
  • Develop scalable cloud-native services, serverless functions (e.g., AWS Lambda), and integration layers.
  • Design and implement event-driven solutions using messaging technologies such as Kafka, Amazon SQS, or similar message bus platforms.
  • Write efficient SQL queries, optimize database performance, and support data integration activities.
  • Follow secure coding standards, software development lifecycle (SDLC) best practices, and code quality guidelines.
  • Develop automated unit, integration, and regression tests using Test-Driven Development (TDD) practices.
  • Build and maintain CI/CD pipelines to automate application deployment and delivery.
  • Troubleshoot production issues, participate in incident response, and provide ongoing application support.
  • Collaborate with product owners, architects, QA, and DevOps teams throughout the software development lifecycle.
  • Participate in code reviews, technical design discussions, and continuous improvement initiatives.
Required Skills & Qualifications
  • 6+ years of professional full-stack software development experience.
  • Strong proficiency in C#/.NET and React development.
  • Experience with JavaScript, HTML, CSS, and modern front-end frameworks.
  • Strong SQL skills, including query optimization, performance tuning, and database development.
  • Experience building RESTful APIs, middleware, and enterprise integration services.
  • Hands-on experience with event-driven architectures using Kafka, Amazon SQS, or similar messaging technologies.
  • Experience developing cloud-native applications and serverless solutions (e.g., AWS Lambda).
  • Knowledge of secure coding practices, application security, and software quality standards.
  • Experience with CI/CD pipelines, source control (Git), and DevOps tools.
  • Experience with Test-Driven Development (TDD) and automated testing frameworks.
  • Familiarity with Agile/Scrum methodologies and modern software engineering practices.
  • Strong analytical, communication, troubleshooting, and problem-solving skills.
  • Ability to work independently while collaborating effectively within cross-functional teams.
Preferred Qualifications
  • Experience with AWS cloud services and cloud architecture.
  • Knowledge of microservices architecture and distributed systems.
  • Experience supporting production applications and incident management.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Experience with performance optimization, monitoring, and application observability tools.

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