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Data Engineer Jobs in Springfield, OH (NOW HIRING)

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services. * Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services. * Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA ...

Booz Allen Hamilton, Inc.

Data Analyst

Beavercreek, OH · On-site

$61K - $141K/yr

The role involves analyzing and reverse-engineering business and technical artifacts to capture, store, and maintain metadata for systems within the portfolio. The Data Analyst may also develop and ...

Booz Allen Hamilton

Data Analyst

Beavercreek, OH · On-site

$61K - $141K/yr

The role involves analyzing and reverse-engineering business and technical artifacts to capture, store, and maintain metadata for systems within the portfolio. The Data Analyst may also develop and ...

Booz Allen Hamilton, Inc.

Data Analyst

Beavercreek, OH · On-site +1

$61K - $141K/yr

The role involves analyzing and reverse-engineering business and technical artifacts to capture, store, and maintain metadata for systems within the portfolio. The Data Analyst may also develop and ...

Northern Trust

Data Platform Engineer

London, OH

$99K - $169K/yr

About Northern Trust As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world's most ...

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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Springfield, OH

Data Engineer information

See Springfield, OH salary details

$40.1K

$116.8K

$159.9K

How much do data engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for data engineer in Springfield, OH is $116,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,100.00 and $123,900.00 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 Springfield, OH? The most popular types of Data Engineer jobs in Springfield, OH are:
What job categories do people searching Data Engineer jobs in Springfield, OH look for? The top searched job categories for Data Engineer jobs in Springfield, OH are:
What cities near Springfield, OH are hiring for Data Engineer jobs? Cities near Springfield, OH with the most Data Engineer job openings:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Springfield, OH as of June 2026, with employment types broken down into 2% As Needed, 87% Full Time, 7% Part Time, 3% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $116,841 per year, or $56.2 per hour.
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Dayton, OH • Remote

Full-time

Posted 10 days ago

Job description

Overview

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.
Education/Qualifications

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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#LI-Remote

Employment Type: FULL_TIME

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