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Data Engineer Jobs in Bryan, TX (NOW HIRING)

Tamus

RIS Senior Data Analyst

College Station, TX · On-site

$7.0K/mo

Job Title RIS Senior Data Analyst Agency Texas A&M University Department Research Info Systems ... What we want The RIS Senior Software Engineer, under general supervision, develops and maintains ...

New

US Modules

Production Engineer

College Station, TX

... data and implement corrective actions based on trends. Equipment & Cross-Functional Collaboration - Work closely with Maintenance and Equipment Engineering to improve equipment performance and ...

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All JobsData Engineer JobsData Engineer Jobs in Bryan, TX

Data Engineer information

See Bryan, TX salary details

$41K

$119.6K

$163.7K

How much do data engineer jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data engineer in Bryan, TX is $119,609.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $126,800.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

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.

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 pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
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What cities near Bryan, TX are hiring for Data Engineer jobs? Cities near Bryan, TX with the most Data Engineer job openings:
Data Engineer jobs near you
Senior Data Engineer (Python and Palantir)

Senior Data Engineer (Python and Palantir)

MM International

Lyons, TX • On-site

$82K - $99K/yr

Contractor

Re-posted 27 days ago

Job description

Job Title:- Senior Data Engineer (Python and Palantir)
Location:- Spring, TX 77389 (On-Site)
Job Type:- Long Term Contract
Could be On-Site Interview
Oil & gas experience is preferred
 
Job Overview:

  • As part of the CCS100 Fusion Team, help build tools that optimize investment and operational decisions in the world-class, scalable carbon capture system that the client is building on the US Gulf Coast.
  • Implement the data layer of the CCS100 application using the Palantir Foundry platform, revising the current design implemented in other technologies.
  • Serve as a knowledge resource regarding Palantir tools for the rest of the CCS100 team.

Key Responsibilities:

  • Quickly come up to speed on the current data organization of the CCS100 product, converting that data model into a Palantir Ontology representation
  • Give suggestions and recommendations on changes to the data model that would improve performance, extensibility, or flexibility of the Palantir solution
  • Set up ingestion and export relationships from the Ontology into other data sources or data stores, ensuring reliability and performance of the connection
  • Implement validations and transforms of the Ontology data as required, taking full advantage of Foundry platform capabilities
  • Create examples or write interface code that will ease connection to Ontology data from other parts of our system

Qualifications:

  • Bachelor’s degree in computer science, engineering, quantitative sciences, or mathematics; alternatively significant practical software project experience
  • Multiple years of experience in building data-heavy applications and/or working as a data engineer
  • Demonstrated proficiency and experience with building applications in Palantir Foundry with focuse on data modeling and utilization of Ontology Manager tool
  • Experienced with using Python to process or transform data
  • Strong analytical thinking skills with ability to assimilate software architectures and data designs quickly
  • Adaptability to rapidly changing priorities and an ability to deliver work on time
  • Good technical communication and collaboration skills; experience working in Agile teams

Preferred Qualification:a

  • Broad experience in other Palantir Foundry tools (e.g. Workshop, Quiver, etc.)

Top 3 Skill Sets/Technologies Required for Qualification:

  • Strong Data Engineering skills and ability to build complex applications applying data science concepts
Palantir Foundry with focus on data modeling and utilization of Ontology Manager tool