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Data Engineer Jobs in Springfield, MA (NOW HIRING)

Senior Data Engineer

Hartford, CT · Hybrid

$106K - $145K/yr

As an experienced Senior Data Engineer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity ...

Travelers Data Engineering team constructs pipelines that contextualize and provide easy access to data by the entire enterprise. As a Senior Data Engineer you will accelerate growth and ...

Showing results 21-40

Data Engineer information

See Springfield, MA salary details

$44.3K

$129.3K

$176.9K

How much do data engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data engineer in Springfield, MA is $129,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,000.00 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, MA?

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

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

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

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

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

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

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

Infographic showing various Data Engineer job openings in Springfield, MA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $129,263 per year, or $62.1 per hour.

Senior Data Engineer - Credit Data Analytics

MDAEdge

Hartford, CT • On-site

$115K - $138K/yr

Full-time

Re-posted 4 days ago


Job description

Job Summary:
MDAEdge is a company focused on delivering enterprise-wide capabilities and complex data solutions. The Senior Data Engineer will drive data engineering efforts, direct code design, and collaborate with teams to implement complex data solutions across multiple systems.
Responsibilities:
• The Corporate Audit and Credit Review (CACR) analytics & automation team delivers data-driven, risk-based insights and automation solutions to the CACR organization. The Senior Data Engineer role will be responsible for developing and implement a range of analytics and automation solutions, including data extraction, analysis, reporting, and dashboard design, but could include more advanced analytics including statistical analysis, text mining & NLP, and modeling/machine learning/AI. This role demands interaction with highly experienced audit and/or credit professionals, data experts and technology. Intellectual curiosity will drive critical thinking to produce optimal solutions. Strong time management, coordination, communication, and presentation skills are a must in this role.
• Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems.
• Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality.
• Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement.
• Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines
• Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes.
• Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes.
• Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls.
• Utilizes sound, seasoned analytical skills to independently develop analytics & automated testing solutions using a variety of tools (Alteryx, Tableau, etc.) and programming languages (SQL, SAS, Python, etc.)
• Supports the design and execution of new analytics, automated testing tools, and models.
• Responsible for multiple projects simultaneously, ensuring each one is completed on time and efficiently with a high standard of work.
• Coordinates, schedules, scopes, and leads large, cross-functional analytics & automation activities.
• Exercises judgment, critical thinking, and sound communication skills to influence business partners.
• Coaches/trains junior team members in execution of analytics and automation activities.
• This position may also have responsibilities for managing associates. Here all managers at this level demonstrate the following responsibilities, in addition to those specific to the role, listed above.
• Diversity & Inclusion Champion: Models an inclusive environment for employees and clients, aligned to company D&I goals.
• Manager of Process & Data: Demonstrates deep process knowledge, operational excellence and innovation through a focus on simplicity, data-based decision making and continuous improvement.
• Enterprise Advocate & Communicator: Communicates enterprise decisions, purpose, and results, and connects to team strategy, priorities and contributions.
• Risk Manager: Ensures proper risk discipline, controls and culture are in place to identify, escalate and debate issues.
• People Manager & Coach: Provides inspection, coaching and feedback to motivate, differentiate and improve performance.
• Financial Steward: Actively manages expenses and budgets in alignment with objectives, making sound financial decisions.
• Enterprise Talent Leader: Assesses talent and builds bench strength for roles across the organization.
• Driver of Business Outcomes: Delivers results by effectively prioritizing, inspecting and appropriately delegating team work.
Qualifications:
Required:
• Intermediate to advanced knowledge of one or more of the following: SQL, SAS, Alteryx, Python, Tableau or related tools.
• Advanced skills in Microsoft Excel.
• Advanced analytic skills that demonstrate the ability to navigate systems, access data, reconcile numbers from different sources, identify discrepancies and trends, and understand drivers of changes within data
• Strong track record of implementing automated solutions related to data & analytics, including the ability to extract, organize, and present the data in user-friendly reports, dashboards or tools.
• Ability to work both independently or in teams on multiple projects simultaneously to deliver timely and complete solutions under minimal supervision.
• Strong written and oral communication skills, with ability to communicate with both technical and executive audience.
Preferred:
• Experience with one or more of the following as plus: model development, machine learning/artificial intelligence (AI), and data science
• Experience with one or more of the following a plus: DataRobot, Instabase, and UIPath.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.