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Data Integrity Engineer Jobs in Massachusetts (NOW HIRING)

Beacon Biosignals

Principal Data Engineer

Boston, MA · On-site +1

$190K - $210K/yr

You hold the Datastore to ever higher standards for data integrity, design soundness, and ... data engineering, data platforms, and infrastructure for data-centric applications * Strong ...

aPriori Technologies Inc

Senior Data Engineer

Concord, MA · On-site

$116K - $157K/yr

Ensure data integrity, quality, and efficiency by applying best practices and tools * Explore and ... Strong hands-on experience in data engineering or software engineering roles * Experience with ...

Liberty Mutual

Senior Data Engineer

Boston, MA · Hybrid

$115K - $156K/yr

... data integrity * Develop automated tests across multiple scopes (Unit, System, Integration ... Collaborate with engineers and architects, and actively contribute to code reviews and engineering ...

Babel Street

Data Warehouse Software Engineer

Somerville, MA

$125K - $150K/yr

We are looking for a motivated Software Engineer I to join our data team! In this role, you will ... Ensure data integrity and consistency across data marts by writing validation queries and row-count ...

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Data Integrity Engineer information

What is the difference between Data Integrity Engineer vs Data Quality Analyst?

AspectData Integrity EngineerData Quality Analyst
Primary FocusEnsuring accuracy, consistency, and security of data across systemsAssessing and improving data quality, completeness, and usability
Skills & CertificationsDatabase management, SQL, data governance, certifications like CDMPData analysis, data profiling, quality frameworks, certifications like CDMP
Work EnvironmentIT teams, data engineering, database administrationBusiness analysis, data analysis teams, quality assurance
Industry UsageTech, finance, healthcare, where data security is criticalRetail, marketing, finance, focusing on data usability

While both roles focus on data, Data Integrity Engineers primarily ensure data security and consistency across systems, whereas Data Quality Analysts focus on assessing and improving data quality for business insights. Both roles often collaborate but serve distinct functions within data management.

What are the key skills and qualifications needed to thrive as a data integrity engineer, and why are they important?

To thrive as a Data Integrity Engineer, you need strong analytical skills, a background in computer science or information systems, and experience with data management principles. Familiarity with database platforms (such as SQL), data validation tools, and knowledge of regulatory compliance standards are typically required. Attention to detail, problem-solving ability, and effective communication help ensure data accuracy and facilitate collaboration across teams. These skills are critical for maintaining reliable, secure, and compliant data systems that support informed business decisions.

What is a data integrity engineer?

Data Integrity Engineers are professionals responsible for ensuring the accuracy, consistency, and reliability of data within an organization’s systems. They design and implement processes to prevent data corruption, loss, or unauthorized modification. These engineers work closely with database administrators, data analysts, and IT teams to monitor data flows, validate data quality, and enforce data governance policies. Their role is crucial in industries where high-quality data is essential for decision-making, compliance, and operational efficiency.

What are some common challenges data integrity engineers face when ensuring data quality across large, complex systems?

Data Integrity Engineers often encounter challenges such as managing data consistency across multiple databases, identifying and resolving discrepancies caused by data migrations, and ensuring compliance with regulatory standards. Additionally, they must frequently collaborate with software developers and database administrators to implement automated validation processes and address data anomalies promptly. Staying updated with evolving best practices and tools is crucial, as data environments and requirements can change rapidly in large organizations.

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

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

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

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

Data Integrity Engineer jobs near you
Infographic showing various Data Integrity Engineer job openings in Massachusetts as of June 2026, with employment types broken down into 82% Full Time, 14% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Infrastructure & ML Engineer (Hybrid Role)

Axcelis

Beverly, MA • Hybrid

$122K - $183K/yr

Full-time

Re-posted 9 days ago

Job description

JOB DESCRIPTION

Job Description: Data Infrastructure & ML Engineer (Hybrid Role)

Role Summary

We are seeking a Senior Data Infrastructure & Machine Learning Engineer to design and implement scalable data systems and pipelines that support advanced analytics and machine learning workflows.

This is a hybrid role where the primary focus is on data pipeline engineering and Python-based data processing, supported by strong database design and management expertise.

Role Focus (Approximate Split)

  • Data Pipeline Engineering & Data Flow (Critical): ~50%
  • Python & Machine Learning Data Processing: ~30%
  • Database Design & Management: ~20%

Key Responsibilities

1. Data Pipeline Engineering (Primary Responsibility)

  • Design and build end-to-end data pipelines (ETL/ELT) for ingesting, processing, and transforming data.
  • Handle multiple data sources including:
    • Tool-generated logs (e.g., AT log files)
    • JSON and semi-structured data
  • Ensure full data traceability, enabling backward tracking of all data points.
  • Implement validation, monitoring, and error handling to ensure data quality and reliability.

2. Database Design & Data Architecture

  • Design and manage scalable database schemas.
  • Support both single-node and distributed database environments.
  • Implement tablespaces, partitioning, and sharding strategies to ensure performance and scalability.
  • Optimize queries and maintain high performance for large-scale datasets.

3. Python-Based Data Processing & Analytics

  • Develop data processing workflows using Python.
  • Work extensively with dataframes for transformation and analysis.
  • Utilize libraries such as:
    • Pandas, NumPy for data manipulation
    • Plotly (or similar) for visualization and exploratory analysis
  • Automate data workflows and integrate them into pipelines.

4. Machine Learning Data Enablement

  • Prepare and transform datasets for machine learning models.
  • Collaborate with data scientists and engineers to support model training and deployment workflows.
  • Enable scalable data foundations for AI/ML integration into production systems.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field with 5+ years of experience.
  • Strong experience in database design and SQL-based systems.
  • Hands-on experience with distributed systems, partitioning, and sharding.
  • Proven experience building data pipelines (ETL/ELT).
  • Strong proficiency in Python for data processing.
  • Experience working with log-based and semi-structured data (e.g., JSON).
  • Understanding of data traceability, validation, and governance.

Preferred Qualifications

  • Experience with time-series or log analytics systems.
  • Exposure to real-time/streaming architectures (e.g., Kafka).
  • Experience with cloud platforms (Azure, AWS, or GCP).
  • Familiarity with machine learning workflows and lifecycle.
  • Domain experience in semiconductor or high-throughput systems (nice to have).

Key Competencies

  • Strong problem-solving and analytical skills.
  • Ability to design production-grade, scalable systems.
  • Focus on data integrity, performance, and reliability.
  • Effective collaboration across engineering and data teams.
  • Clear communication and documentation.

EQUAL OPPORTUNITY STATEMENT


It is the policy of Axcelis to provide equal opportunity in all areas of employment for all persons free from discrimination based on race, sex, religion, age, color, national origin, disability status, medical condition (including pregnancy), veteran status, sexual orientation, marital status, or any other characteristic protected by federal, state or local law. Axcelis will provide reasonable accommodation necessary to enable a disabled candidate or employee to perform the essential functions of the position, unless the accommodation would create an undue hardship for the Company.

U.S. BASE SALARY RANGE

$122,133.07 - $183,199.61

This base salary range reflects the typical compensation for this role across U.S. locations.

Our salary ranges are determined by role and level; individual pay is determined based on

multiple factors, including job-related skills, experience, relevant education or training, work

location, and internal equity. The range provides the opportunity for growth and progression as

you develop within the role.

Base pay is one part of our U.S. total compensation package which includes eligibility in the

Axcelis Team Incentive bonus plan, and comprehensive benefits package (for regular

employees working 20+ hours a week).

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