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Data Engineer Jobs in Clemson, SC (NOW HIRING)

Td

Data Scientist III - FCRM

Greenville, SC

$96K - $155K/yr

Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract ...

Td

Data Scientist II (US) FCRM Modeling

Greenville, SC · On-site

Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract ...

Global Lending Services

Data Scientist

Greenville, SC · On-site

As a Data Scientist at GLS, you will play a vital role in addressing critical business challenges ... Proficiency in programming and working with open-source AI/ML languages and tools, including but ...

Lockheed Martin

Data Analyst Sr- Level 3

Greenville, SC · On-site +1

$76K - $96K/yr

The Greenville Quality Engineering Team within Lockheed Martin Aerospace is seeking a senior data scientist analyst who will play a key role in developing, deploying, and maintaining data based ...

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All JobsData Engineer JobsData Engineer Jobs in Clemson, SC

Data Engineer information

See Clemson, SC salary details

$37.7K

$109.9K

$150.4K

How much do data engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for data engineer in Clemson, SC is $109,908.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $116,500.00 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
What are the most commonly searched types of Data Engineer jobs in Clemson, SC? The most popular types of Data Engineer jobs in Clemson, SC are:
What cities near Clemson, SC are hiring for Data Engineer jobs? Cities near Clemson, SC with the most Data Engineer job openings:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Clemson, SC as of July 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 100% In-person job distribution, with an average salary of $109,908 per year, or $52.8 per hour.
Data Engineering Lead- Finance

Data Engineering Lead- Finance

DPR Construction

Greenville, SC

$107K - $129K/yr

Full-time

Posted 7 days ago

DPR Construction rating

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

21st of 80 rated construction

Job description

Job DescriptionWe are a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to streamline operations, enhance decision-making, and drive efficiency across all levels. We are looking for a talented Data Engineer to join our team and contribute to developing robust data solutions that support our business goals.
This role is ideal for someone who enjoys combining technical problem-solving with stakeholder collaboration. You will collaborate with business leaders to understand data needs and work closely with a global engineering team to deliver scalable, timely, and high-quality data solutions that power insights and operations.
Responsibilities
  • Own data delivery for specific business verticals by translating stakeholder needs into scalable, reliable, and well-documented data solutions.
  • Participate in requirements gathering, technical design reviews, and planning discussions with business and technical teams.
  • Partner with the extended data team to define, develop, and maintain shared data models and definitions.
  • Design, develop, and maintain robust data pipelines and ETL processes using tools like Azure Data Factory and Python across internal and external systems.
  • Proactively manage data quality, error handling, monitoring, and alerting to ensure timely and trustworthy data delivery.
  • Perform debugging, application issue resolution, root cause analysis, and assist in proactive/preventive maintenance.
  • Support incident resolution and perform root cause analysis for data-related issues.
  • Create and maintain both business requirement and technical requirement documentation
  • Collaborate with data analysts, business users, and developers to ensure the accuracy and efficiency of data solutions.
  • Collaborate with platform and architecture teams to align with best practices and extend shared data engineering patterns.
Qualifications
  • Minimum of 4 years of experience as a Data Engineer, working with cloud platforms (Azure, AWS).
  • Proven track record of managing stakeholder expectations and delivering data solutions aligned with business priorities.
  • Strong hands-on expertise in Azure Data Factory, Azure Data Lake, Python, and SQL
  • Familiarity with cloud storage (Azure, AWS S3) and integration techniques (APIs, webhooks, REST).
  • Experience with modern data platforms like Snowflake and Microsoft Fabric.
  • Solid understanding of Data Modeling, pipeline orchestration and performance optimization
  • Strong problem-solving skills and ability to troubleshoot complex data issues.
  • Excellent communication skills, with the ability to work collaboratively in a team environment.
  • Familiarity with tools like Power BI for data visualization is a plus.
  • Experience working with or coordinating with overseas teams is a strong plus
Preferred Skills
  • Knowledge of Airflow or other orchestration tools.
  • Experience working with Git-based workflows and CI/CD pipelines
  • Experience in the construction industry or a similar field is a plus but not required.

DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.

Working at DPR, you'll have the chance to try new things, explore unique paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.

Explore our open opportunities atwww.dpr.com/careers.

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