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Data Engineer Jobs in Grapevine, TX (NOW HIRING)

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Role - Data Engineer • 2-3 years of hands-on experience in Data Engineering • Strong experience in Python and PySpark/Spark for large-scale data processing • Experience working with Databricks ...

Data Engineer

Fort Worth, TX · On-site

$45 - $50/hr

Data Engineer (Contract - Hybrid) Location: Irving, TX (Hybrid - 3 days onsite) Pay: $45-$50/hour Duration: Contract Work Authorization: , or Authorized to Work in the U.S. Position Overview Seeking ...

Data Engineer

Irving, TX · On-site

$100 - $120K/hr

Data Engineer -Pay Range: $100-$120K -Location: Dallas-Fort Worth, TX -Benefits: Medical, Dental, Vision, 401(k) We are looking to bring on a 3-6 year Data Engineer to our growing team. What we will ...

Data Engineer

Irving, TX · On-site

$100 - $120K/hr

Data Engineer -Pay Range: $100-$120K -Location: Dallas-Fort Worth, TX -Benefits: Medical, Dental, Vision, 401(k) We are looking to bring on a 3-6 year Data Engineer to our growing team. What we will ...

Data Engineer

Irving, TX · On-site

$100 - $120K/hr

Data Engineer -Pay Range: $100-$120K -Location: Dallas-Fort Worth, TX -Benefits: Medical, Dental, Vision, 401(k) We are looking to bring on a 3-6 year Data Engineer to our growing team. What we will ...

Data Engineer

Plano, TX · On-site

$109K - $131K/yr

Data Engineer Location: Plano, TX (Onsite) looking for an experienced Data Engineer to build and maintain scalable data pipelines and analytics solutions leveraging AWS services such as Athena ...

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

This is a hands-on engineering role with a focus on data modeling, transformation, and scalability. Key Responsibilities * Design, implement, and maintain robust ETL/ELT pipelines to ingest and ...

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

The Data Engineer role is responsible for designing, building, and maintaining scalable data pipelines, integrations, and data models that support enterprise reporting, analytics, data migration, and ...

Data Engineer

Irving, TX · On-site

$109K - $132K/yr

Senior Data Engineer Location: Irving, TX, Only Locals Work Model: Hybrid 3 Days Onsite per Week Experience: Min 10 Years We are looking for a Data Engineer with strong expertise in Databricks ...

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

As a Data Engineer, you'll be the visionary behind our data platforms, crafting them into powerful tools for decision-makers. Your role? Ensuring a treasure trove of pristine, harmonized data is at ...

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

The Data Engineer role is responsible for designing, building, and maintaining scalable data pipelines, integrations, and data models that support enterprise reporting, analytics, data migration, and ...

Data Engineer - Hybrid

Irving, TX · On-site +1

$75K - $130K/yr

Data Engineer We are looking for a Data Engineer who is passionate about building scalable data systems and enabling highquality analytics, machine learning, and business intelligence. In this role ...

Data Engineer

Dallas, TX · On-site

$60 - $65/hr

Data Engineer Location: Dallas, TX Job Summary: As a Databricks Lead, you will be a critical member of our data engineering team, responsible for designing, developing, and optimizing our data ...

Data Engineer - Hybrid

Irving, TX · On-site

$75K - $130K/yr

Data Engineer We are looking for a Data Engineer who is passionate about building scalable data systems and enabling high-quality analytics, machine learning, and business intelligence. In this role ...

Data Engineer

Fort Worth, TX · On-site

$109K - $131K/yr

Sr. Data Engineer - Fort Worth, TX (3 Days Onsite) Description: Minimum Qualifications- Education & Prior Job Experience 5-7 years software solution development using agile, DevOps, operating in a ...

Data Engineer - Hybrid

Irving, TX · On-site +1

$75K - $130K/yr

Data Engineer We are looking for a Data Engineer who is passionate about building scalable data systems and enabling high‑quality analytics, machine learning, and business intelligence. In this ...

Data Engineer

Irving, TX · On-site

$110K - $133K/yr

Job Title: Data Engineer - MEM SQL Location: New Jersey / Irving, TX / Tampa, FL We are looking for an experienced Data Engineer with strong expertise in MEM SQL (SingleStore) to join our team ...

Data Engineer

Frisco, TX · On-site

$116K - $135K/yr

The Data Engineer will enable trusted, AI-ready data foundations and support client- and vendor-facing technology solutions that are critical to business operations, growth, and service delivery.

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Data Engineer information

See Grapevine, TX salary details

$41.1K

$119.8K

$164K

How much do data engineer jobs pay per year?

As of Jun 29, 2026, the average yearly pay for data engineer in Grapevine, TX is $119,842.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,800.00 and $127,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
What are the most commonly searched types of Data Engineer jobs in Grapevine, TX? The most popular types of Data Engineer jobs in Grapevine, TX are:
What are popular job titles related to Data Engineer jobs in Grapevine, TX? For Data Engineer jobs in Grapevine, TX, the most frequently searched job titles are:
What job categories do people searching Data Engineer jobs in Grapevine, TX look for? The top searched job categories for Data Engineer jobs in Grapevine, TX are:
What cities near Grapevine, TX are hiring for Data Engineer jobs? Cities near Grapevine, TX with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Grapevine, TX as of June 2026, with employment types broken down into 2% As Needed, 90% Full Time, 5% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,842 per year, or $57.6 per hour.
Data Engineer

Data Engineer

Programmers.io

Dallas, TX • On-site

$113K - $136K/yr

Full-time

Posted 9 days ago


Job description

Role - Data Engineer

• 2–3 years of hands-on experience in Data Engineering
• Strong experience in Python and PySpark/Spark for large-scale data processing
• Experience working with Databricks and Delta Lake architecture
• Good understanding of SQL (PostgreSQL) and NoSQL databases (MongoDB, Redis)
• Exposure to Kafka Streaming or real-time data processing frameworks
• Experience with Azure or AWS cloud platforms
• Understanding of data partitioning, performance tuning, and in-memory optimizations
• Experience working in Linux/Unix environments
• Knowledge of CI/CD pipelines and production deployment practices
• Familiarity with REST APIs and application development concepts
• Understanding of software design patterns and system architecture
• Exposure to multi-user data platforms and access management
• GenAI exposure (preferred): understanding of LLM workflows, prompt versioning, evaluation frameworks
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