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Data Engineer Jobs in Bryan, TX (NOW HIRING)

About this opportunity We are seeking a highly motivated and skilled Data Center Optical Engineer to lead work in customer environments and co-locations. The person in this role is responsible for ...

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 ...

As a Data Center Technician, you will execute rack-and-stack activities, structured cabling ... Ability to interpret engineering drawings, installation documentation, and methods of procedure ...

As a Data Center Technician, you will execute rack-and-stack activities, structured cabling ... Ability to interpret engineering drawings, installation documentation, and methods of procedure ...

Job Title Utilities Data Analyst Agency Texas A&M University Department Utilities & Energy Services ... Bachelor's degree in related area such as engineering, statistics, mathematics, etc., or equivalent ...

Support PLC, SCADA, HMI, data acquisition, and industrial network systems throughout manufacturing ... Partner with operations, maintenance, engineering, and IT teams to identify automation ...

Who we are Engineering has been part of Texas A&M University since its opening in 1876 as the ... Implement real-time data acquisition from sensors (thermocouples, load cells, encoders, imaging ...

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Data Engineer information

See Bryan, TX salary details

$41K

$119.6K

$163.7K

How much do data engineer jobs pay per year?

As of Sep 5, 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.

What is a data engineer?

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.

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.

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 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.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

What are the most commonly searched types of Data Engineer jobs in Bryan, TX?

The most popular types of Data Engineer jobs in Bryan, TX are:

What are popular job titles related to Data Engineer jobs in Bryan, TX?

For Data Engineer jobs in Bryan, TX, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Bryan, TX look for?

The top searched job categories for Data Engineer jobs in Bryan, TX are:

What cities near Bryan, TX are hiring for Data Engineer jobs?

Cities near Bryan, TX with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Bryan, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $119,609 per year, or $57.5 per hour.

Senior Data Engineer (Python and Palantir)

MM International

Lyons, TX โ€ข On-site

$82K - $99K/yr

Contractor

Re-posted 14 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