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Remote Data Engineer Jobs in Garner, NC (NOW HIRING)

Senior Data Engineer

Raleigh, NC · Remote

$103K - $140K/yr

... functional data science and engineering teams. * Design and deploy intelligent retrieval ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

Principal Data Scientist

Raleigh, NC · On-site +1

$147K - $243K/yr

Work closely with data engineering and ML Ops functional roles to operationalize data science ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

... IL, Remote-MI, Remote-NJ, St. Louis, Missouri Details Kemper is one of the nation's leading ... Enterprise Data Engineering * Artificial Intelligence & Intelligent Automation * Enterprise ...

AI Engineer

Raleigh, NC · Remote

$130K - $160K/yr

AI Engineer, location is remote in the Raleigh, NC area with onsite collaboration as needed. The ... Support data accessibility initiatives tied to the client's internal data warehouse and ETL ...

Showing results 21-40

Remote Data Engineer information

See Garner, NC salary details

$39.7K

$115.6K

$158.2K

How much do remote data engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for remote data engineer in Garner, NC is $115,626.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,100.00 and $122,600.00 per year, depending on experience, location, and employer.

What does a remote data engineer do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a remote data engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

What are the key skills and qualifications needed to thrive as a remote data engineer, and why are they important?

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.

What are the most commonly searched types of Data Engineer jobs in Garner, NC?

The most popular types of Data Engineer jobs in Garner, NC are:

What job categories do people searching Remote Data Engineer jobs in Garner, NC look for?

The top searched job categories for Remote Data Engineer jobs in Garner, NC are:

What cities near Garner, NC are hiring for Remote Data Engineer jobs?

Cities near Garner, NC with the most Remote Data Engineer job openings:

Infographic showing various Remote Data Engineer job openings in Garner, NC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $115,626 per year, or $55.6 per hour.

Senior Data Engineer

Redhat

Raleigh, NC • Remote

$103K - $140K/yr

Full-time

Posted 10 days ago


Job description

*Telecommuting role to be performed anywhere in the U.S.

Architect and implement complex, high-volume data pipelines between Snowflake and Databricks utilizing PySpark for distributed data processing and dbt for SQL-based data transformation, including developing macro-driven data quality tests and validation frameworks.

What You Will Do:

  • Orchestrate pipeline scheduling, dependency management, and automated failure recovery using Apache Airflow to deliver B2B marketing attribution and multi-touch targeting analytics.
  • Administer the enterprise Databricks platform by configuring IAM roles for secure Amazon S3 bucket access, managing application credentials and secrets through Databricks' built-in vault system and OpenShift secrets, and establishing workspace governance policies and cluster configurations for cross-functional data science and engineering teams.
  • Design and deploy intelligent retrieval architecture and AI-driven workflows using vector-based search methods and enterprise data platforms, building marketing retrieval and decision-automation applications that integrate multiple data sources and APIs.
  • Operationalize MLOps methodologies using MLflow for experiment tracking and model registry management, and Lakehouse monitoring for automated post-production model performance tracking to optimize predictive accuracy and increase marketing return on investment.
  • Implement end-to-end machine learning models and deliver stakeholder-facing analytical outputs by building Named Entity Recognition (NER) systems using TextBlob, gensim, and fastText for enterprise systems analysis, developing predictive models using XGBoost and Scikit-learn, constructing deep learning architectures using Keras, and designing time-series forecasting models for event-based user adoption prediction.
  • Manage CI/CD pipelines using Git and Tekton to ensure reliable, repeatable code delivery for production applications.
  • Build and manage container images using buildah and skopeo, pushing to internal container registries for deployment.
  • Lead the deployment and maintenance of containerized data science models and enterprise applications on Red Hat OpenShift (Kubernetes), managing network routes, TLS termination, and container orchestration for highavailability services.
  • Lead application security initiatives by completing comprehensive enterprise security compliance assessments encompassing 20+ security controls across the full technology stack, aligned with industry frameworks such as NIST and CIS Controls.
  • Perform static application security testing (SAST) using SonarQube, execute vulnerability scanning using Qualys and pip-audit, complete Privacy Impact Assessments (PIA), and conduct STRIDE-based threat modeling.
  • Collaborate with enterprise information security teams to remediate identified vulnerabilities, navigate compliance audits, and maintain centralized logging and monitoring through Splunk.

What You Will Bring:

  • Master's degree (U.S. or foreign equivalent) in Computer Science or related field and three (3) years of experience in the job offered or related role OR Bachelor's degree (U.S. or foreign equivalent) in Computer Science or related field and five (5) years of experience in the job offered or related role.
  • Must have three (3) years of experience with: architecting and implementing high-volume data pipelines between cloud data warehouse (Snowflake) and lakehouse (Databricks) platforms using PySpark for distributed data processing and dbt for SQL-based data transformation, including developing macro-driven data quality test frameworks and validation logic; orchestrating and scheduling data pipeline workflows using Apache Airflow, including configuring DAG-based dependency management, automated failure recovery, and pipeline monitoring for enterprise analytics workloads; administering enterprise Databricks environments, including configuring IAM roles for secure cloud object storage (Amazon S3) access, managing application secrets through platform vault systems and OpenShift secrets, and establishing workspace governance and cluster policies for cross-functional teams; implementing end-to-end machine learning models by: 1) building Named Entity Recognition (NER) systems using TextBlob, gensim, and fastText for enterprise text analysis; 2) developing predictive models using gradient boosting frameworks (XGBoost) and Scikit-learn; 3) constructing deep learning architectures using Keras; and 4) designing time-series forecasting models for event-based prediction; delivering full-scale information retrieval systems for enterprise data by researching, evaluating, and implementing Transformer architectures and Transfer Learning methodologies using deep learning frameworks for semantic search, text classification, and vector-based clustering; operationalizing MLOps methodologies using MLflow for experiment tracking and model registry management, and implementing automated post-production model monitoring to track performance degradation and optimize predictive accuracy; managing CI/CD pipelines using Git and Tekton, building and publishing container images using buildah and skopeo to internal container registries, and deploying containerized applications on Red Hat OpenShift (Kubernetes) with network route management, TLS termination, and high-availability configurations; and leading enterprise security compliance assessments, including performing static application security testing (SAST) using SonarQube, executing vulnerability scans using Qualys, completing Privacy Impact Assessments (PIA), and conducting STRIDE-based threat modeling.

#LI-DNI

The salary range for this position is $158,309 - $180,000/year. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.


About Red Hat

Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Inclusion at Red Hat
Red Hat's culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.


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