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Data Integration Manager Jobs in Malden, MA (NOW HIRING)

Accenture

OneStream Integration Lead

Boston, MA · On-site

Develop and configure OneStream Data Management workflows including Import, Export, Transform, and ... Perform integration testing, data reconciliation, and validation across financial periods.

Cooley

Content Integration Manager

Boston, MA · On-site

Content Integration Manager Cooley is seeking a Content Integration Manager to join the Marketing ... client data * High level of professionalism at all times * Demonstrated ability to lead through ...

Aveva

Integration Change Lead

Cambridge, MA · On-site

$148K - $247K/yr

Gather post feedback and refine enablement approaches based on adoption data and employee input. Integration Communications (Supportive, Not Primary) * In coordination with the Integration Manager ...

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All JobsData Integration JobsData Integration Manager JobsData Integration Manager Jobs in Malden, MA

Data Integration Manager information

See Malden, MA salary details

$10

$53

$87

How much do data integration manager jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for data integration manager in Malden, MA is $53.90, according to ZipRecruiter salary data. Most workers in this role earn between $45.38 and $60.67 per hour, depending on experience, location, and employer.

What are some common challenges a data integration manager faces when coordinating cross-departmental projects?

Data Integration Managers often encounter challenges such as aligning different departments' data standards, managing conflicting priorities, and ensuring data security across systems. Effective communication and strong project management skills are essential for navigating these complexities. Building collaborative relationships and setting clear expectations early in the project can help streamline data flows and minimize bottlenecks.

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

To thrive as a Data Integration Manager, you need expertise in data management, ETL processes, and a strong understanding of database systems, often supported by a degree in computer science or a related field. Familiarity with integration tools like Informatica, Talend, or Microsoft SSIS, as well as experience with cloud platforms and relevant certifications, is typically required. Strong leadership, problem-solving skills, and effective communication help manage cross-functional teams and stakeholder expectations. These skills ensure seamless data flow, system reliability, and successful project delivery in complex data environments.

What is the difference between Data Integration Manager vs Data Analyst?

AspectData Integration ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications in data management or integration toolsBachelor's degree in Statistics, Mathematics, or related field; certifications in data analysis or visualization tools
Work EnvironmentCollaborates with IT teams, data engineers, and business units to oversee data integration processesWorks with business stakeholders to analyze data, generate reports, and support decision-making
Employer & Industry UsageCommon in tech, finance, healthcare, and large enterprises managing complex data systemsWidely used across industries for data-driven roles focusing on insights and reporting

While both roles involve working with data, the Data Integration Manager focuses on overseeing the integration and management of data systems, ensuring data flows correctly across platforms. In contrast, the Data Analyst primarily interprets data to generate insights and support business decisions. Both roles require strong technical skills, but their core responsibilities and focus areas differ significantly.

What is a data integration manager?

A data integration manager oversees the process of combining data from different sources into a unified system, ensuring data quality and consistency. They often work with tools like ETL (Extract, Transform, Load) processes and require strong project management and technical skills. Their role involves coordinating teams, managing data workflows, and implementing integration solutions to support business analytics and decision-making.

What cities near Malden, MA are hiring for Data Integration Manager jobs?

Cities near Malden, MA with the most Data Integration Manager job openings:

Data Integration Manager jobs near you
Infographic showing various Data Integration Manager job openings in Malden, MA as of June 2026, with employment types broken down into 76% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $112,119 per year, or $53.9 per hour.

Senior Data Integration Operations Engineer

The Chronicle Of Higher Education, Inc.

Boston, MA • On-site

$150 - $200/hr

Other

Posted 19 days ago

Key responsibilities

  • Monitor data integration pipelines, detect incidents, and coordinate resolution to ensure reliable data flow.

  • Administer and maintain data integration platform environments, including job scheduling, connector configuration, and platform updates.

  • Analyze performance metrics, identify bottlenecks, and implement tuning to optimize data pipeline performance.

Job description

Senior Data Integration Operations Engineer

Summary: Northeastern University seeks an experienced Sr. Data Integration & Operations Engineer to manage daily data integration pipelines and processes. The role oversees ETL/ELT workflows on enterprise platforms, ensuring reliable data flow from source systems into the data lakehouse and downstream solutions. Requires hands-on expertise in data integration platform administration, pipeline operations, data observability, incident management, and continuous improvement in production environments.

Key Responsibilities & Accountabilities
  • Pipeline Monitoring, Observability, and Incident Management: Monitor pipeline health, data freshness, volume, and job completion using observability tools. Detect and resolve incidents, coordinate with source system owners and technical teams, and ensure timely recovery to minimize impact.
  • Operational Support and Maintenance: Administer and maintain data integration platform environments (Informatica and related tools), including job scheduling, connector configuration, data refreshes, and platform patching. Manage integration jobs feeding the data lakehouse and downstream solutions. Schedule maintenance with minimal disruption and manage user access per security policies.
  • Performance Analysis and Optimization: Analyze performance metrics, identify bottlenecks and long-running jobs, implement tuning. Contribute to the data observability platform strategy, metrics, SLAs, and alert rules.
  • Documentation and Knowledge Management: Create and maintain operational documentation, runbooks, SOPs, and knowledge articles. Document system configurations, data pipeline dependencies, and recovery procedures.
  • Continuous Improvement and Automation: Identify opportunities to automate repetitive tasks, improve reliability, and reduce manual intervention. Develop scripts and workflows; evaluate tools (including Fivetran) and evolve data integration practices.
  • Position Type: Information Technology
  • Additional Information: Northeastern University offers comprehensive benefits for benefit-eligible employees. See Northeastern HR benefits information for details. All qualified applicants are encouraged to apply and will be considered without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other protected characteristic. Compensation ranges and hiring details are provided by the university.
Minimum Qualifications
  • Data Integration Platform Experience: Hands-on experience administering and operating enterprise data integration platforms, with Informatica PowerCenter or IDMC strongly preferred. Experience with SaaS-based ELT tools such as Fivetran is a plus. Ability to manage complex integration workflows, configure connectors, and troubleshoot end-to-end.
  • Data Pipeline Operations: Extensive experience maintaining, scheduling, and troubleshooting data integration pipelines from enterprise sources (ERP, SIS, CRM, HR, finance) to data lakehouse and downstream applications. Strong SQL/Python for data validation and investigation. Familiarity with lakehouse concepts and schema management.
  • Data Observability and Pipeline Monitoring: Experience with data observability platforms or equivalent monitoring tools tracking data freshness, volume, quality, and schema changes. Proficiency in designing alerting frameworks with meaningful signals and minimal noise.
  • Incident Management: Strong experience in troubleshooting and resolving AI system and data infrastructure issues, with ability to prioritize by business impact.
  • Performance Optimization: Techniques for resource allocation, scaling, and tuning of AI systems and data pipelines.
  • Change Management: Experience implementing changes to production AI systems and pipelines with testing, validation, and rollback procedures.
  • Data Quality Management: Understanding of data quality principles and remediation of issues such as missing records, nulls, duplicates, schema drift, and late-arriving data. Detect data quality failures before affecting downstream consumers.
  • Documentation and Knowledge Management: Excellence in creating and maintaining operational documentation and runbooks.
  • Automation Skills: Ability to create automation scripts and workflows to streamline routine operational tasks for AI and data pipelines.
  • DevOps Practices: Familiarity with DevOps and CI/CD for AI systems, including containerization, orchestration, and infrastructure as code.
  • Security Awareness: Understanding of security best practices for AI operations and data handling, including access control and vulnerability management.
  • Collaboration Skills: Ability to work with cross-functional teams and coordinate incident response effectively.
  • Problem-solving: Strong analytical and problem-solving skills for troubleshooting complex issues.
  • Compliance Knowledge: Understanding of regulations affecting AI systems and data processing in higher education.
  • Communication Skills: Clear written and verbal communication to document procedures and report incidents.
  • Service Management: Knowledge of IT service management principles and applying them to AI and data pipeline operations.
  • Education and Experience: Bachelor's degree in Computer Science, IT, Data Management, or related field; technical certifications preferred. Minimum 4-5 years in data integration, data engineering operations, or related IT operations with hands-on ETL/ELT production experience. Experience with cloud platforms (AWS, Azure, GCP) and data lakehouse/platforms (Snowflake, Databricks, Microsoft Fabric, Delta Lake). Understanding of medallion architecture, incremental loads, and schema evolution.
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