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Data Processing Jobs in Massachusetts (NOW HIRING)

Verisk

Data Architect

Boston, MA · On-site

$160K - $175K/yr

The ideal candidate will bring strong expertise in AWS data services, big data processing, data modeling, enterprise analytics, and cloud-native architectures . This role requires a hands-on ...

Roberts Recruiting

Data Engineer

Boston, MA

$124K - $149K/yr

... processing technologies. Responsibilities for this role include: * Implement data engineering best-practices to build extraction, loading, and transformation logic to land large datasets into the ...

Solomon Page

Sr. Data Engineer

Boston, MA · On-site

$50 - $65/hr

Refactor existing ETL processes to improve performance, scalability, and reliability. * Perform extensive data validation, testing, and quality assurance across data platforms. * Optimize PostgreSQL ...

Ikigai

Data Scientist

Cambridge, MA · On-site

... processes. • Partner with internal engineering and success teams to ensure smooth implementations and knowledge transfer. Qualifications : Required : • At least 1-3 years of experience in a data ...

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All JobsData Processing JobsData Processing Jobs in Massachusetts

Data Processing information

See Massachusetts salary details

$13

$22

$38

How much do data processing jobs pay per hour?

As of Jul 1, 2026, the average hourly pay for data processing in Massachusetts is $22.13, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $24.42 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Processing position, and why are they important?

To thrive in Data Processing, you need strong analytical abilities, attention to detail, and proficiency with spreadsheets and database management, often supported by an associate's degree or relevant experience. Familiarity with tools like Microsoft Excel, SQL, or data entry software, as well as certifications such as Certified Data Processor (CDP), are frequently expected. Strong organizational skills, time management, and the ability to troubleshoot problems efficiently are valued soft skills. These competencies are crucial for ensuring data accuracy, meeting deadlines, and supporting smooth information operations within an organization.

What is a data processing job role?

A data processing job involves collecting, organizing, and converting raw data into a usable format for analysis or reporting. It often requires skills in data management tools, attention to detail, and knowledge of data formats and software such as Excel, SQL, or specialized processing programs.

What are the typical daily responsibilities of someone working in Data Processing?

A typical day for a Data Processing professional involves entering, validating, and updating records in databases or spreadsheets to ensure data integrity. You may also be responsible for generating reports, cleaning large data sets, and identifying discrepancies or errors for correction. Collaboration with team members or departments is common to clarify data requirements and resolve issues. Staying organized and attentive to detail is essential because the quality of processed data can impact decision-making across the organization.

What is a Data Processing job?

A Data Processing job involves collecting, organizing, and managing data to ensure accuracy and accessibility. Professionals in this role use software tools to input, clean, analyze, and process data for businesses or organizations. They may also generate reports and automate workflows to streamline data handling. Strong attention to detail and proficiency in data management tools are essential for success in this field.

Is AI replacing data entry jobs?

AI is automating many data entry tasks by using machine learning and optical character recognition, which can increase efficiency and reduce manual labor. However, data processing jobs still require human oversight for complex or unstructured data, and roles involving data validation, analysis, and management remain essential. Professionals in data processing should develop skills in AI tools and data management to stay relevant.

What is the highest paying job in data?

In data-related fields, roles such as Data Science Director, Chief Data Officer, or Senior Data Architect tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with extensive experience and relevant certifications.
What are the most commonly searched types of Data Processing jobs in Massachusetts? The most popular types of Data Processing jobs in Massachusetts are:
What are popular job titles related to Data Processing jobs in Massachusetts? For Data Processing jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Data Processing jobs in Massachusetts look for? The top searched job categories for Data Processing jobs in Massachusetts are:
What cities in Massachusetts are hiring for Data Processing jobs? Cities in Massachusetts with the most Data Processing job openings:
Data Processing jobs near you
Sr Data Engineer- Data Platform & AI Enablement

Sr Data Engineer- Data Platform & AI Enablement

Citizens

Boston, MA • On-site

$124K - $149K/yr

Other

Posted 21 days ago

Key responsibilities

  • Design, build, and maintain secure, scalable, and efficient data pipelines and platforms to acquire, transform, and store large datasets.

  • Develop and optimize data models and pipelines to support analytics, reporting, machine learning, and AI-driven use cases, including AI/GenAI-ready data capabilities.

  • Collaborate with cross-functional teams to deliver data solutions, troubleshoot and resolve data-related issues, and ensure data quality, observability, and adherence to compliance standards.

Job description

Description

Senior Data Engineer - Enterprise Data Enablement

The Enterprise Data Enablement team is seeking a Senior Data Engineer who can design, develop, and maintain secure, scalable, and efficient data pipelines and platforms. This role will focus on building and deploying data solutions across financial consumer business domains by leveraging existing and new data framework capabilities to acquire, transform, stream, and integrate data. The candidate will also contribute to innovative data engineering solutions, including AI/GenAI/Agentic AI-ready data capabilities, while collaborating with and supporting a team of data engineers in building scalable, secure, and intelligent data platforms.

Primary Responsibilities
  • Design, build, and maintain reliable, efficient, and scalable data pipelines to acquire, transform, and store large datasets.
  • Develop robust data pipelines to collect, process, and compute metrics from various financial data sources while adhering to quality and development standards.
  • Contribute to application architecture and technical solutions, and help implement data framework patterns alongside senior engineers and architects.
  • Collaborate with cross-functional teams to deliver optimal data solutions that meet business and platform needs.
  • Develop and deploy high-quality, production-ready code.
  • Apply strong database design principles and data modeling techniques to translate business requirements into scalable data solutions.
  • Develop and optimize data models to support analytics, reporting, machine learning, and AI-driven use cases.
  • Support the implementation and enhancement of enterprise data frameworks and contribute to scalable solutions.
  • Identify opportunities to improve existing frameworks and help build reusable capabilities across the organization.
  • Troubleshoot and resolve data-related issues in a timely manner.
  • Execute unit testing for data pipelines, validate results, and ensure data quality and accuracy; partner with business users for User Acceptance Testing and support deployment activities.
  • Follow change management practices and ensure adherence to compliance and regulatory standards.
  • Design and build data pipelines and platform capabilities that support AI, Generative AI, and Agentic AI use cases, including model training, inference, retrieval, and orchestration workflows.
  • Enable AI-ready data foundations by developing high-quality, governed, and reusable datasets for machine learning, large language model (LLM), and intelligent automation solutions.
  • Develop and optimize pipelines for structured, semi-structured, and unstructured data to support GenAI use cases such as semantic search, document intelligence, and retrieval-augmented generation (RAG).
  • Partner with data scientists, ML engineers, architects, and product teams to integrate AI/GenAI capabilities into enterprise data platforms and workflows.
  • Implement metadata, lineage, governance, security, and access controls required for responsible AI and enterprise-scale GenAI adoption.
  • Ensure observability, reliability, performance, and data quality for data pipelines, including those supporting AI-enabled workflows.
Required Skills / Experience
  • 6-8+ years of experience in data engineering and distributed data processing technologies.
  • Hands-on experience with streaming technologies such as Apache Spark, Beam, or Flink.
  • Experience with message brokers such as Apache Kafka.
  • Experience working with microservices and batch processing systems.
  • Strong programming skills in Java and/or Scala; Python experience preferred.
  • Strong SQL development and performance optimization skills.
  • Solid knowledge of relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL databases (MongoDB or similar).
  • Experience with CI/CD pipelines and version control systems such as Bitbucket and Git.
  • Experience with ETL development tools such as Talend or DataStage is a plus.
  • Experience with Java Spring Boot; familiarity with React, TypeScript, or Angular is a plus.
  • Understanding of cloud-based data processing, with AWS and/or Azure experience preferred.
  • Experience building data pipelines that support analytics, machine learning, and AI workloads.
  • Working knowledge of data engineering concepts supporting LLM-based applications, including retrieval pipelines, embeddings workflows, and unstructured data processing.
  • Familiarity with AI/GenAI concepts such as RAG, semantic search, document processing, and model inference workflows.
  • Understanding of data governance, security, lineage, and compliance requirements, particularly in regulated environments.
  • Exposure to workflow orchestration frameworks and automation patterns is a plus.
  • Exposure to vector databases, semantic models, or MLOps/LLMOps concepts is a plus.
  • Strong analytical and problem-solving skills, with the ability to collaborate effectively within technical teams.
Education, Certifications, and/or Other Professional Credentials
  • Bachelor's degree in Computer Science, Engineering, or a related technology field
Hours and Work Schedule
  • Hours per Week: 40
  • Work Schedule: Monday through Friday

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Education:Why Work for UsEmployment Type: 1ST

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