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Data Validator Jobs in Massachusetts (NOW HIRING)

Lead Data Modeler

Boston, MA · On-site

$125 - $150/hr

Validate incoming data against expected mappings and ensure alignment with defined models. * Act as the primary owner of how legacy data translates into the unified system. Data Quality ...

New

Validate incoming data against expected mappings and ensure alignment with defined models. * Act as the primary owner of how legacy data translates into the unified system. * Data Quality ...

Validate incoming data against expected mappings and ensure alignment with defined models. * Act as the primary owner of how legacy data translates into the unified system. * Data Quality ...

Data Quality Analyst

Andover, MA · On-site

$24 - $30/hr

Perform data profiling, validation, and cleansing to ensure high-quality datasets * Identify, investigate, and resolve data discrepancies and anomalies * Develop and maintain data quality metrics ...

Data Engineer CO-OP

Boston, MA · On-site

$30 - $34/hr

Provide data validation and data quality assessments. * Identify and resolve data anomalies. COMPETENCIES: * Proficient in SQL and Python required. * Familiarity with Java a plus. * Familiarity with ...

Data Engineer Co-Op

Boston, MA · On-site

$30 - $34/hr

Provide data validation and data quality assessments. * Identify and resolve data anomalies. COMPETENCIES: * Proficient in SQL and Python required. * Familiarity with Java a plus. * Familiarity with ...

Data Analytics Co-Op

Boston, MA · On-site

$30 - $34/hr

Provide data validation and data quality assessments. * Identify and resolve data anomalies. COMPETENCIES: * Proficient in Power BI and SQL required. * Experience designing and implementing optimal ...

Financial Data Analyst

Woburn, MA · On-site

$90K - $104K/yr

Collect, clean, and analyze financial and operational data from multiple internal systems; use AI-assisted tools (including Claude) to accelerate data validation, anomaly detection, and cross-source ...

Financial Data Analyst

Canton, MA · On-site

$90K - $104K/yr

Collect, clean, and analyze financial and operational data from multiple internal systems; use AI-assisted tools (including Claude) to accelerate data validation, anomaly detection, and cross-source ...

Data Arch - Snowflake

Somerville, MA · On-site

$125K - $150K/yr

Experience performing data profiling, data quality analysis, and data validation activities. * Familiarity with data governance, release management, and ITIL processes. * Experience supporting ...

New

Perform data validation and quality checks to ensure information entered is accurate and complete. * Track completed records and maintain organized documentation of research and data entry activities.

Showing results 41-60

Data Validator information

See Massachusetts salary details

$50.2K

$180.2K

$265.9K

How much do data validator jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data validator in Massachusetts is $180,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,800.00 and $185,700.00 per year, depending on experience, location, and employer.

What is a data validator?

A Data Validator is responsible for ensuring the accuracy, consistency, and integrity of data within a system or dataset. They review, clean, and verify data to identify errors, inconsistencies, or missing information. This role is essential in industries that rely on high-quality data for decision-making, such as finance, healthcare, and research. Data Validators use various tools and techniques to cross-check and validate data against predefined standards or business rules. Their work helps maintain data reliability, improves efficiency, and supports better decision-making across an organization.

What skills and qualifications are needed to be a data validator?

To thrive as a Data Validator, you need strong attention to detail, analytical skills, and experience working with large datasets, often supported by a degree in information technology, mathematics, or a related field. Familiarity with data validation tools, database systems (like SQL), Excel, and sometimes industry-standard certifications such as CDMP (Certified Data Management Professional) can be advantageous. Excellent communication, problem-solving abilities, and the capacity to work independently or as part of a team are valuable soft skills. These competencies ensure accuracy, integrity, and reliability in data, which are critical for decision-making and business operations.

What challenges might I face as a data validator, and how can I overcome them?

As a Data Validator, you may encounter challenges like identifying subtle inconsistencies in large datasets, managing tight deadlines for data verification, and adapting to multiple data sources or formats. To overcome these hurdles, it’s important to develop strong troubleshooting skills, stay organized, and leverage automated validation tools whenever possible. Collaborating closely with data engineers and business analysts can also help clarify data requirements and resolve ambiguities. Building a thorough understanding of data processes within your organization will further equip you to handle these challenges effectively and efficiently.

How do I become a data validator?

To become a data validator, you typically need a high school diploma or equivalent, along with strong attention to detail and analytical skills. Gaining experience with data management tools, spreadsheets, and database software can be helpful, and some roles may require a bachelor's degree in a related field such as information technology or computer science. Certifications in data quality or validation can also enhance your qualifications.

What are popular job titles related to Data Validator jobs in Massachusetts?

For Data Validator jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Data Validator jobs in Massachusetts look for?

The top searched job categories for Data Validator jobs in Massachusetts are:

Infographic showing various Data Validator job openings in Massachusetts as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $180,220 per year, or $86.6 per hour.

$125 - $150/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


Job description

We are looking for a highly motivated, systems-oriented Lead Data Modeler to own the design, governance, and evolution of our data warehouse at InterSystems.

This role sits at the center of our data lake / data warehouse initiative and will be responsible for defining how data is structured, understood, and used across the organization. You will work closely with Data Engineering, Sales Tech, CRM, Marketing Technology, and business stakeholders to translate fragmented legacy CRM and operational systems into a unified, scalable data model.

This is a hands‑on role requiring strong SQL and data analysis skills, with an emphasis on data modeling, source-to-target mapping, and cross‑system reconciliation. You will not primarily build ingestion pipelines, but you will define exactly how data should flow, transform, and be represented - serving as the source of truth for all downstream analytics and applications.

In addition to modeling, this role will own core aspects of data governance, user access design, user support, and internal data warehouse administration within InterSystems.

Key Responsibilities Data Modeling & Architecture Ownership
  • Design and maintain conceptual, logical, and physical data models across the data lake / warehouse.
  • Define canonical data definitions, relationships, and business logic across fragmented legacy systems.
  • Build scalable, extensible models that reduce redundancy and support analytics, reporting, and operational workflows.
  • Establish modeling standards, naming conventions, and documentation practices across the platform.
  • Continuously refine models as new data sources and use cases emerge.
Source-to-Target Mapping & Data Translation
  • Analyze legacy CRM and other operational datasets to understand structure, quality, and business meaning.
  • Define detailed source-to-target mapping logic for ingestion into the data model.
  • Provide clear, implementation‑ready transformation specifications to Data Engineers.
  • Validate incoming data against expected mappings and ensure alignment with defined models.
  • Act as the primary owner of how legacy data translates into the unified system.
Data Quality, Reconciliation & Discrepancy Resolution
  • Partner with Data Engineers to identify and resolve discrepancies across systems and pipelines.
  • Develop frameworks for data validation, integrity checks, and consistency monitoring.
  • Investigate edge cases and ambiguous data definitions with SMEs and stakeholders.
  • Establish processes for ongoing data quality governance as the platform scales.
Data Warehouse Administration
  • Maintain and optimize schemas and views within the data warehouse, ensuring high performance and reliability.
  • Support ETL workflows, data integrity checks, and reporting pipelines.
  • Manage user access, roles, and data security within the warehouse environment.
  • Monitor query performance and optimize schemas and indexing strategies.
  • Maintain clear, up-to-date documentation of schemas, tables, and data flows.
Cross-Functional Collaboration & Communication
  • Partner with Sales, CRM, Marketing, and other stakeholders to gather and clarify data requirements.
  • Translate complex data structures into clear, understandable documentation for non-technical users.
  • Work closely with Data Engineering to ensure seamless execution of ingestion and transformation logic.
  • Align with internal teams to standardize definitions and avoid duplication of data efforts.
Platform Growth & Governance
  • Own the onboarding of new data sources into the data warehouse platform.
  • Define scalable patterns for integrating additional systems over time.
  • Establish and manage user groups, access patterns, and data consumption layers.
  • Contribute to long‑term strategy for enterprise data architecture at InterSystems.
Short-Term Goals (0–6 months)
  • Build a comprehensive understanding of existing CRM and operational data sources.
  • Develop the initial unified data model across core systems.
  • Define and document source-to-target mappings for key datasets.
  • Stand up and organize the data warehouse schema.
  • Establish user groups, access controls, and initial governance processes.
  • Partner with Data Engineering to support initial ingestion and validation pipelines.
  • Identify and resolve major discrepancies across legacy systems.
Long-Term Goals (6–24 months)
  • Expand the data model to incorporate additional business domains and data sources.
  • Evolve the platform into a scalable, enterprise‑grade data lake / warehouse.
  • Establish robust data governance, documentation, and quality monitoring frameworks.
  • Enable self‑service analytics through well‑structured and well‑documented datasets.
  • Drive standardization of data definitions across the organization.
  • Continuously optimize performance, usability, and scalability of the platform.
Required Qualifications
  • 5+ years of experience in data modeling, data architecture, or related roles.
  • Strong SQL skills with the ability to independently analyze complex datasets.
  • Experience designing conceptual, logical, and physical data models.
  • Experience working with databases (IRIS, PostgreSQL, or similar).
  • Strong understanding of data normalization, denormalization, and schema design trade‑offs.
  • Experience defining source-to-target mappings and working with ETL/ELT processes.
  • Ability to work with ambiguous, messy legacy data and derive structured solutions.
  • Strong attention to detail and commitment to data accuracy and consistency.
Preferred Qualifications
  • Experience working with CRM or customer data platforms.
  • Familiarity with InterSystems IRIS or similar enterprise data platforms.
  • Experience supporting data governance, access control, and data quality initiatives.
  • Proficiency in Python for data analysis or validation workflows.
  • Experience using AI tools to accelerate data analysis, mapping, and documentation.
  • Strong communication skills with the ability to work across technical and business teams

We are an equal‑opportunity employer and do not discriminate because of race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. InterSystems is an E‑Verify Employer in the United States.

InterSystems is providing a current good faith estimate of the anticipated base salary range for this position depending on a variety of factors including experience, education, skills, and performance.

Other compensation may include a discretionary annual variable target incentive.

The company also provides generous employee benefits including:

  • Medical, vision, and dental insurance
  • Short‑term and long‑term disability, and life insurance
  • 401(k) Profit Sharing Contribution
  • Paid Time Off and Holidays
  • Parental Leave
  • Tuition reimbursement

The estimated base compensation range for this role is:

$126,000 — $163,000 USD

About InterSystems

InterSystems, a creative data technology provider, delivers a unified foundation for next‑generation applications for healthcare, finance, manufacturing, and supply chain customers in more than 80 countries. Our data platforms solve interoperability, speed, and scalability problems for large organizations around the globe to unlock the power of data and allow people to perceive data in imaginative ways. Established in 1978, InterSystems is committed to excellence through its 24×7 support for customers and partners around the world. Privately held and headquartered in Boston, Massachusetts, InterSystems has 38 offices in 28 countries worldwide. For more information, please visit InterSystems.com.

AI Disclaimer

InterSystems may use AI tools for its internal operations including administrative tasks during recruitment (e.g., organizing candidate information). InterSystems’ approach to AI is guided by the InterSystems Responsible AI Guidelines. AI is not used to make or influence hiring decisions. All decisions are made by InterSystems employees.

Candidates may use AI for CV or interview preparation, provided materials are truthful and reflect their own experience. AI tools and third‑party transcription services must not be used during interviews or assessments.

Please note that the use of wearable technology, including any AI‑related tools or other technology‑connected devices (such as META or Google smart glasses and/or wearables, and/or any similar devices), is strictly prohibited during the interview and screening process with InterSystems. Any applicant who requires a wearable device or any type of technology support during the interview process as a reasonable accommodation under the ADA or applicable state or country laws and regulations must contact the InterSystems Human Resources Department prior to attending or participating in any interview or screening process.

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