1

Data Engineer Jobs in West Virginia (NOW HIRING)

Data Science and Data Engineering Job Qualifications: Skills: Change Management, Data Quality, Governance Framework, Governance Structures, Process Governance Certifications: None Experience: 10 + ...

Experience programming with Python, SQL, R, or other analytics-focused programming languages to develop scalable business solutions. * Experience working with relational databases, cloud data ...

Data Science and Data Engineering Job Qualifications: Skills: Data Analytics, Python for Data Analysis, Statistical Analysis Certifications: None Experience: 4 + years of related experience US ...

GovCIO is seeking a Journeyman Systems Engineer to support a critical government computer system ... Coast Guard (USCG) Data & AI Integration Team. This role is primarily responsible for building ...

Coast Guard (USCG) Data & AI Integration Team. This role is primarily responsible for building ... As a Journeyman Systems Engineer, you will serve as a core technical resource for deploying ...

Data Reporting and Analytics Lead

WV · On-site +1

$169K - $229K/yr

Data Science and Data Engineering Job Qualifications: Skills: Business Intelligence Tools, Data Analysis, Data Modeling, Data Reporting, Datasets Certifications: None Experience: 10 + years of ...

SAP Data Migration Engineer

WV · Remote

$97K - $127K/yr

Yes GDIT has an opportunity for an SAP Data Migration Engineer to support the SAP S/4HANA transformation programs through direct execution of data migration activities. The position focuses on ...

WV · On-site

Partner with data engineers and architects to validate data models, transformations, and reporting logic. * Ensure requirements incorporate data classification, security, and access control ...

WV · On-site

Data Science and Data Engineering Job Qualifications: Skills: Artificial Intelligence (AI), End-to-End Testing, Machine Learning (ML) Certifications: None Experience: 5 + years of related experience ...

Showing results 41-60

Data Engineer information

See West Virginia salary details

$34.5K

$100.4K

$137.4K

How much do data engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data engineer in West Virginia is $100,422.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,600.00 and $106,400.00 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.

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 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.

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.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipelines. 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 and proficiency with tools like SQL, Python, and cloud platforms.

What are the most commonly searched types of Data Engineer jobs in West Virginia?

The most popular types of Data Engineer jobs in West Virginia are:

What are popular job titles related to Data Engineer jobs in West Virginia?

For Data Engineer jobs in West Virginia, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in West Virginia look for?

The top searched job categories for Data Engineer jobs in West Virginia are:

What cities in West Virginia are hiring for Data Engineer jobs?

Cities in West Virginia with the most Data Engineer job openings:

What are popular job titles related to Data Engineer jobs in WV?

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

Infographic showing various Data Engineer job openings in West Virginia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $100,422 per year, or $48.3 per hour.

Forward Deployed Engineer - AI/ML Data Science

Cengage Learning

Charleston, WV

$106K - $127K/yr

Full-time

Posted 21 days ago


Job description

We believe in the power and joy of learning

At Cengage, our employees have a direct impact in helping learners around the world discover the power and joy of learning. We are bonded by our shared purpose - driving innovation that helps millions of learners improve their lives and achieve their dreams through education.

About This Role

Cengage is at an inflection point. As we scale our AI-powered learning ecosystem including Student Assistant, AI faculty insights, and Cengage Unlimited the gap between a polished platform demonstration and a deeply embedded, outcomes-driving deployment at an institution is where the real work lives. The Lead Field Development Engineer closes that gap.

As a Lead FDE, you will embed directly with Cengage's most strategic institutional partners to architect, configure, and ship production-grade AI and platform solutions tailored to their academic, compliance, and pedagogicalenvironments. This is not a sales engineering role: you will write and own production code, influence Cengage's core platform roadmap with field-derived insights, mentor other engineers, and establish the standard for complex institutional AI deployments.

What You'll Own
STRATEGIC INSTITUTIONAL DEPLOYMENT

  • Embed with 3-5 strategic institutional accounts at a time, working directly with partners to understand instructional workflows, legacy LMS architectures, and institutional data environments before proposing a solution

  • Lead end-to-end delivery of MindTap AI, WebAssign, Cengage Unlimited, and custom GenAI integrations from discovery through production launch and ongoing iteration

  • Design and build institution-specific configurations including adaptive learning paths, RAG-backed course assistants, and auto-graded problem banks that address pedagogical challenges at scale

  • Drive LTI 1.3 and LTI Advantage integrations between Cengage platforms and institutional LMS environments such as Canvas, Blackboard, D2L, and Moodle, including SSO, grade passback, and data flows

TECHNICAL ARCHITECTURE & ENGINEERING

  • Write production-quality code in Python, JavaScript/TypeScript, and SQL to build integration middleware, data pipelines, and custom tooling that extend Cengage's core platforms

  • Architect and deploy agentic AI workflows using LLM APIs and retrieval-augmented generation pipelines grounded in institutional course content

  • Build and maintain automated evaluation frameworks that measure the accuracy, safety, and pedagogical quality of AI-generated student guidance at the institution level

  • Ensure deployments meet FERPA, WCAG 2.1 AA accessibility, institutional data-governance requirements, and Cengage's AI safety standards

  • Translate field-derived deployment patterns, integration heuristics, and failure modes into first-class contributions to Cengage's product and engineering roadmap

LEADERSHIP & ENABLEMENT

  • Serve as the technical authority for field deployment practices, establishing standards, reusable integration templates, and a shared knowledge base of institutional patterns

  • Mentor junior and mid-level FDEs and conduct technical reviews of deployment architectures, code, and
    stakeholder communication

  • Partner closely with Cengage product managers, platform engineers, content teams, Sales, and Customer Success to prioritize roadmap features and define technical success criteria

  • Present deployment architecture, outcomes data, and AI safety posture to institutional CIOs, Chief
    Academic Officers, and VP-level stakeholders with authority and clarity

  • Define adoption milestones and renewal-driving outcomes for strategic accounts, ensuring technical delivery translates into measurable institutional value

WHAT YOU'LL BUILD IN YOUR FIRST 12 MONTHS

  • A reference deployment architecture for Cengage AI and LTI 1.3 integration that can serve as the team standard across institutions

  • Custom RAG-powered course-assistant deployments embedded inside MindTap for strategic university
    partners, with measurable engagement and learning-outcome targets

  • An automated AI evaluation harness for Cengage Student Assistant covering accuracy, academic-
    integrity safety, and response quality across FDE-managed accounts

  • A faculty analytics integration layer connecting Student Assistant interaction data to institutional LMS gradebooks and early-alert systems

  • A library of reusable integration modules for Canvas, Blackboard, D2L, and Moodle that reduces institutional onboarding time from weeks to days

What You Bring

TECHNICAL

  • 7+ years of software engineering experience with a track record of shipping production systems in complex, customer-facing environments

  • 3+ years in a customer-embedded or field-facing engineering role such as FDE, Solutions Engineer, Applied AI Engineer, or Implementation Architect, with ownership of full deployments rather than demonstrations along

  • Strong full-stack engineering skills, including Python, JavaScript/TypeScript, REST or GraphQL API design, and modern application frameworks

  • Hands-on experience building and deploying LLM-based applications in production, including RAG pipelines, prompt engineering, tool-calling agents, and evaluation frameworks

  • Demonstrated experience with LMS integration standards such as LTI 1.3, LTI Advantage, AGS, NRPS, and Deep Linking

  • Proficiency with cloud platforms; AWS is preferred, with experience across services such as Lambda, ECS or EKS, RDS or Aurora, S3, API Gateway, and CloudWatch

  • Working knowledge of learning analytics standards such as xAPI or Caliper and educational data-privacy frameworks including FERPA, COPPA, and applicable state requirements

LEADERSHIP & COMMUNICATION

  • Demonstrated ability to translate ambiguous institutional requirements into a concrete technical plan, own the plan end to end, and remain accountable for outcomes

  • Experience presenting technical architecture and AI product strategy to C-suite and senior academic leadership, with credibility in both engineering and executive settings

  • Track record of mentoring engineers and raising the technical bar of a team, not only executing individual work

  • Comfort with up to 30% travel to institutional partner sites throughout the academic year

Preferred Qualifications

  • Experience in higher education technology, edtech, or academic publishing, including an understanding of how universities procure, adopt, and measure learning technology

  • Familiarity with adaptive learning platforms, learning engineering, and learning-science research

  • Experience with enterprise AI governance frameworks, responsible AI evaluation, and AI safety in production deployments

  • Contributions to open-source projects, published technical writing, or conference presentations related to AI deployment, platform engineering, or edtech

  • AWS Certified Solutions Architect, Google Cloud Professional Machine Learning Engineer, or an equivalent certification

  • Graduate degree in Computer Science, Data Science, Educational Technology, or a related field

Cengage is committed to working with broad talent pools to attract and hire strong and most qualified individuals. Our job applicants are considered regardless of any classification protected by applicable federal, state, provincial or local laws.

Cengage is also committed to providing reasonable accommodations for qualified individuals with disabilities including during our job application process. If you are an applicant with a disability and require reasonable accommodation in our job application process, please contact us at accommodations.ta@cengage.com.

About Cengage

Cengage, a global education technology company serving millions of learners, provides affordable, quality digital products and services that equip students with the skills and competencies needed to be job ready. For more than 100 years, we have enabled the power and joy of learning with trusted, engaging content, and now, integrated digital platforms. We serve the higher education, workforce skills, secondary education, English language teaching and research markets worldwide. Through our scalable technology, including MindTap and Cengage Unlimited, we support all learners who seek to improve their lives and achieve their dreams through education.

Compensation

At Cengage Group, we take great pride in our commitment to providing a comprehensive and rewarding Total Rewards package designed to support and empower our employees. Click here to learn more about our Total Rewards Philosophy.

The full base pay range has been provided for this position. Individual base pay will vary based on work schedule, qualifications, experience, internal equity, and geographic location. Sales roles often incorporate a significant incentive compensation program beyond this base pay range.

In this position, you will be eligible to participate in the company'sdiscretionaryincentive bonus program. This position's bonus target amount, which is not guaranteed and is dependent on individual performance and overall company results among other factors, is provided below.

15% Annual: Individual Target$117,100.00 - $187,300.00 USD