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Data Engineer Jobs in Springfield, MO (NOW HIRING)

Sr. Cloud Data Engineer

Springfield, MO · On-site

$96K - $131K/yr

Senior Cloud Data Engineer Internal Job Summary Join our Data Engineering team as a Senior Cloud Data Engineer, where you will lead the development and implementation of data pipelines for our cloud ...

Principal AI Engineer Location: Springfield, Missouri Department: Information Technology Employment ... This hands-on role develops natural language-to-SQL solutions, semantic data models, and prototype ...

This hands-on role develops natural language-to-SQL solutions, semantic data models, and prototype ... Principal AI Engineer, LLM, Snowflake, Cortex AI, natural language to SQL, semantic data modeling ...

We're looking for a creative, systems-thinking engineer with strong data platform expertise ... excellent SQL/Python skills, and a passion for translating business questions into scalable AI ...

Principal AI Engineer Location: Springfield, Missouri Department: Information Technology Employment ... Five reasons to apply: opportunity to lead AI strategy across the data platform; handson work with ...

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

This position works closely with AI leadership, Data Science, MLOps, Data Engineering, Product/Delivery, Security, Privacy, Store Operations, Merchandising, and other cross-functional partners to ...

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Data Engineer information

See Springfield, MO salary details

$40.5K

$118K

$161.5K

How much do data engineer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data engineer in Springfield, MO is $117,994.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,200.00 and $125,100.00 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 Springfield, MO?

The most popular types of Data Engineer jobs in Springfield, MO are:

What are popular job titles related to Data Engineer jobs in Springfield, MO?

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

What job categories do people searching Data Engineer jobs in Springfield, MO look for?

The top searched job categories for Data Engineer jobs in Springfield, MO are:

What cities near Springfield, MO are hiring for Data Engineer jobs?

Cities near Springfield, MO with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Springfield, MO as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $117,994 per year, or $56.7 per hour.

Senior Data Engineer I

Springfield, MO • On-site


HEARTLAND BUSINESS SYSTEMS LLC

8.6

Company rating: 8.6 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

33rd of 225 rated it services

People enjoy working here

Good employer


$90K - $122K/yr

Full-time

Re-posted 6 days ago


Job description

Description

Position Summary:

This position would require a candidate to possess a strong technical background in developing and delivering BI solutions along with a strong understanding of SQL Server environments. Business intelligence (BI) is a set of technologies and practices for transforming business information into actionable reports and visualizations. The Senior Data Engineer transforms data into a useful format for analysis and is focused on the design and architecture.

A Senior Data Engineer is the data professional who prepares the data infrastructure to be leveraged by the HBS BI Data Developers. The Senior Data Engineer will design, build, integrate data from various resources and manage big data. The Senior Data Engineer ensures the operations of the data pipeline follow a consistent process of Ingestion, Processing, Storage and Access. The work involves tuning databases for fast analysis and creating table schemas.

The Senior Data Engineer is responsible for making data easily accessible, ensuring the process works smoothly and is optimized. The Senior Data Engineer is a critical firm member of the Data Team, The Senior Data Engineer will run Extract, Transform and Load (ETL) on top of datasets and create data warehouses that can be used for reporting and analysis. The Senior Data Engineer ensures the operations of the data pipeline follow a consistent process of Ingestion, Processing, Storage and Access.

Roles and Responsibilities/ Essential Functions:

  •  Meet with clients to understand their current business processes and needs to provide consulting services and direction on how to build or grow their current data strategy.
  •  Work with HBS Sales Solutions consultants to identify and grow opportunities within HBS client environments.
  •  Support and administer the underlining infrastructure and layout of a client data environment.
  •  Develop and design the process for the customer data collection process.
  •  Develop policies and procedures for the collection and analysis of data.
  •  Review customer sources to ensure integrity of the data collection process.
  •  Collaborate with the BI Data Developers to ensure the requirements are being met to build the right solution needed.
  •  Estimate development effort required to deliver data customer needs and requests.
  •  Use business analysis skillset to identify development needs for the purpose of streamlining and improving the operations of the organization for efficiency and profitability.
  •  Ability to work independently or as a team on project-based solutions for clients.
  •  Work with team mates to continue to grow and mature data services and delivery options for HBS clients.
  •  Based on experience, one may mentor other engineers in developing scalable, secure, high-performance BI and Data solutions.
  •  Meet annual billable hour goal, as defined by HBS. This number may change over time as the business evolves. 


Requirements

Competencies:

  •  Accuracy - Ability to produce high quality work deliverables leveraging industry best practices.
  •  Analytical Skills - Strong abilities required to effectively interpret customer business needs and translate them into application and operational requirements, resolving complex technical and business problems.
  •  Communication - strong written, verbal, and non-verbal communication skills, especially conveying complex information in an understandable manner.
  •  Leadership - Ability to motivate and guide others to ensure performance is in accordance with clear expectations and goals.
  •  Learning - Ability to quickly learn new technologies to deliver solutions.
  •  Presentation Skills - Ability to effectively conduct formal and informal presentations in both small and large group settings within all levels of a company.
  •  Project Management - Ability to demonstrate an understanding of process engineering, planning, organizing, staffing, directing, and controlling work tasks.
  •  Time Management - Ability to effectively utilize available time for managing multiple tasks/projects simultaneously.

Required Experience:

  • 7+ years of experience in technology related role
  • Data Model Design (Physical or Conceptual or both)
  • Experience with needs analysis, software evaluation and selection, customization, and implementation
  • Data Warehousing systems and architecture experience in 'real world', practical, successful implementations
  • Understand multi-dimensional/relational database structures and schemas.
  • Strong knowledge of system design, development, and deployment 
  • Microsoft BI Suite Experience (Excel, Microsoft SQL Server Integration Services (SSIS), Azure Data Factory (ADF), etc.)
  • Programming and Processing Experience (T-SQL, ETL, etc.)
  • Azure Experience in Azure SQL Database or Azure SQL Manage Instance
  • Strong knowledge of SQL utilizing MS SQL Server
  • Expertise in Professional Services or similar client facing roles

Preferred Experience:

  • Experience in multiple industry (Education, Healthcare, Retail, Manufacturing) verticals
  • PowerShell knowledge and understanding
  • Understanding of report writing and visualization
  • GitHub Copilot experience
  • Microsoft BI Suite Experience (Power BI or Fabric)
  • Microsoft certified: Data Analyst Associate
  • Microsoft certified: DP-200 - Implementing an Azure Data Solution 
  • Microsoft certified: DP-201 - Designing an Azure Data Solution
  • Microsoft certified: DP-300 - Administering Relational Databases on Microsoft Azure
  • Other SQL platform knowledge (Oracle, MySQL, PostgreSQL, etc.)

Required Skills, Education and/ or Certifications:

  •  Bachelor's degree in business or I.T. related discipline accepted or equivalent experience

Equal Opportunity Employer - Including Disabled and Veterans

#HBS


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