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Data Engineer Jobs in Amherst, MA (NOW HIRING)

Bespoke Labs

Data Engineer

Springfield, MA · On-site

$114K - $136K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

ISO New England, Inc.

Lead Data Engineer

Holyoke, MA · On-site

$150K - $170K/yr

We have an important role to play in securing the region's clean and reliable energy future and are looking for a Data Engineer to join our team. In this role, you will design, develop, and maintain ...

MassMutual

AI Engineer

Springfield, MA · Hybrid

$141K - $185K/yr

AI Engineer | Data Science & AI Engineering Full-Time Hybrid (3 days/per week in office) The Opportunity MassMutual's AI & Data Science team is seeking a skilled AI Engineer to join our high ...

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All JobsData Engineer JobsData Engineer Jobs in Amherst, MA

Data Engineer information

See Amherst, MA salary details

$43.8K

$127.8K

$174.8K

How much do data engineer jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data engineer in Amherst, MA is $127,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,800.00 and $135,400.00 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 Amherst, MA? The most popular types of Data Engineer jobs in Amherst, MA are:
What cities near Amherst, MA are hiring for Data Engineer jobs? Cities near Amherst, MA with the most Data Engineer job openings:
Data Engineer jobs near you
Data Engineer IV

Data Engineer IV

Farm Credit Financial Partners, Inc.

Springfield, MA

$114K - $137K/yr

Full-time

Re-posted 22 days ago

Job description

POSITION SUMMARY: The Data Engineer IV is responsible for transforming data that can be easily analyzed. The position will be responsible for expanding and optimizing our data and data pipeline for our Association partners. The Data Engineer IV primarily works with project teams on developing new data platforms to support strategic initiatives in alignment with business and/or enterprise strategies.

DUTIES AND RESPONSIBILITIES:

Lead and architect an enterprise-scale data engineering project team in a matrix organization

Provide strategic direction for the design, enhancement, and long-term support of data platforms.

Drive organizational data engineering strategy by influencing process including, : automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build and optimize the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.

Oversee engineering standards through code reviews to ensure quality and best practices are maintained.

Shape enterprise-wide data governance policies, partnering with senior leadership and stakeholders. This includes data quality, data management, data policies, business process management, and risk management surrounding the handling of organizational data.

Other related duties as assigned.

SKILLS AND COMPETENCIES:

Coach and mentor junior engineers

Effectively Communicate technical direction to senior leadership and cross-functional stakeholders. Foster innovative team culture and process improvement during development phase

Demonstrate thought leadership in data engineering practices and enterprise data strategy.

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