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Data Manager Jobs in Springfield, MA (NOW HIRING)

TicketNetwork

Director of Data and AI

South Windsor, CT · On-site

This role serves as the single point of accountability for enterprise data management, governance, and AI-ensuring initiatives are strategically aligned, responsibly governed, and deliver measurable ...

Pwc

Data Engineer - Senior Manager

Hartford, CT · On-site

$124K - $280K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Pwc

AI & GenAI Data Scientist - Manager

Hartford, CT · On-site

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As an AI & GenAI Data Scientist - Manager, you will play a pivotal role in ...

Next Level Business Services, Inc.

Data Modeler

Windsor, CT · On-site

$54.50 - $70.75/hr

Hi, My Name is Ajay Singh and I'm a Resource Manager at Next Level Business Services, Inc. Please ... Data Modeler Location: Hartford/ Windsor, CT Hire Type: Full Time Only - 1) Needs to know ...

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Data Manager information

See Springfield, MA salary details

$30.9K

$96.8K

$171.4K

How much do data manager jobs pay per year?

As of Jun 18, 2026, the average yearly pay for data manager in Springfield, MA is $96,805.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,800.00 and $125,100.00 per year, depending on experience, location, and employer.

What is the salary of a data manager?

The salary of a data manager typically ranges from $70,000 to $120,000 annually, depending on experience, location, and industry. Professionals with advanced skills in database management, data analysis, and certifications like CDMP or CBIP tend to earn higher salaries.

What does a data manager work?

A data manager is responsible for organizing, maintaining, and ensuring the accuracy and security of data within an organization. They often oversee data collection processes, implement data management systems, and use tools like databases and data analysis software. Strong attention to detail and knowledge of data governance are essential for this role.

What is a Data Manager?

A Data Manager is a professional responsible for overseeing the collection, storage, organization, and safeguarding of data within an organization. They ensure that data is accurate, accessible, and secure, often working with databases and data management systems. Data Managers also develop data policies, maintain data quality, and support teams in using data effectively for decision-making. Their role is crucial in industries where large volumes of information are handled, such as healthcare, finance, and research.

What is the difference between Data Manager vs Data Analyst?

AspectData ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like CDMP or DAMA often preferredBachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentTypically manages data systems, databases, and teams; works in IT or data departmentsAnalyzes data sets, creates reports, and visualizations; often works in business or analytics teams
Employer & Industry UsageUsed across industries like healthcare, finance, and tech for data governance and managementCommon in marketing, finance, and consulting for insights and decision-making

While both roles involve working with data, Data Managers focus on overseeing data systems and ensuring data quality, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What Is a Data Manager?

A data manager is responsible for creating and managing databases that meet the specific needs of a company or organization. As a data manager, your job duties include assessing customer database requirements, modifying the structure of existing databases, and handling the backup and recovery of older systems. You should have experience working with many database system varieties and large volumes of customer records. You can find data manager positions in a wide range of industries.

What are the key skills and qualifications needed to thrive as a Data Manager, and why are they important?

To thrive as a Data Manager, you need expertise in data management principles, database administration, and data governance, often supported by a bachelor's degree in computer science or a related field. Familiarity with SQL, data warehousing tools, data visualization platforms, and certifications like CDMP or DAMA are typically required. Strong analytical thinking, attention to detail, and effective communication are essential soft skills for ensuring data integrity and collaborating with stakeholders. These skills and qualifications are crucial for maintaining secure, accurate data systems and supporting informed business decisions.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as data visualization, SQL, and statistical analysis, often through online courses or certifications, regardless of age.

How does a Data Manager typically collaborate with other departments to ensure data integrity?

As a Data Manager, collaboration with various departments—such as IT, analytics, and operations—is essential to maintain data integrity and consistency. You’ll regularly coordinate with these teams to establish data governance protocols, resolve discrepancies, and ensure that data collection and storage meet organizational standards. Open communication and regular meetings help address data quality issues and align data management practices across the organization. This cross-functional work not only supports accurate reporting but also drives better decision-making company-wide.

What is the role of a data manager?

A data manager is responsible for overseeing the collection, storage, organization, and maintenance of data within an organization. They ensure data quality, security, and accessibility, often using database management tools and following data governance standards. Their role supports data analysis and decision-making processes.
More about Data Manager jobs
What are the most commonly searched types of Data jobs in Springfield, MA? The most popular types of Data jobs in Springfield, MA are:
What job categories do people searching Data Manager jobs in Springfield, MA look for? The top searched job categories for Data Manager jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Data Manager jobs? Cities near Springfield, MA with the most Data Manager job openings:
Data Manager jobs near you
Infographic showing various Data Manager job openings in Springfield, MA as of June 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $96,805 per year, or $46.5 per hour.
Director of Data and AI

Director of Data and AI

TicketNetwork

South Windsor, CT • On-site

Full-time

Retirement

Posted 19 days ago

Job description

RCN Capital is a national, direct private lender supporting real estate investors across the country. We're seeking a Director of Data and Artificial Intelligence to define, own, and lead the company's enterprise data, governance, and AI strategy. This role is responsible for transforming data and AI from fragmented tools and isolated efforts into a cohesive, governed, business critical capability that drives operational efficiency, better decision making, and competitive advantage.
RCN has reached a point where data quality, analytics, and AI cannot be implemented by committee. This role serves as the single point of accountability for enterprise data management, governance, and AI-ensuring initiatives are strategically aligned, responsibly governed, and deliver measurable business value.
Responsibilities:
Enterprise Data & AI Strategy
• Define and own RCN Capital's enterprise data and AI vision, strategy, and roadmap, aligned to business priorities and long term growth objectives.
• Serve as the central authority for data governance and AI adoption across the organization.
• Partner with executive leadership to identify how data and AI can transform lending, operations, analytics, and customer experience.
Data Governance, Ownership & Quality
• Establish and enforce an enterprise data governance framework, including principles, policies, standards, and operating model.
• Define clear data ownership, stewardship, and accountability across critical domains (e.g., loans, borrowers, properties, servicing, finance).
• Develop and maintain governance policies covering:
- Data quality (accuracy, completeness, timeliness)
- Data security and access controls
- Data privacy and regulatory compliance
- Data retention and lifecycle management
• Ensure governance is embedded into systems and workflows, preventing bad data at the source rather than correcting it downstream.
• Establish data quality metrics, controls, escalation paths, and dashboards to track improvement over time.
AI Use Case Development & Delivery
• Identify, evaluate, and prioritize high value AI use cases across origination, servicing, capital markets, finance, operations, and corporate functions.
• Lead the design and implementation of:
- Generative AI (LLMs, copilots, agents)
- Predictive and prescriptive analytics
- Automation and decision support solutions
• Ensure AI initiatives move from proof of concept to production grade, scalable capabilities.
Platform, Architecture & Enablement
• Partner with Data, Engineering, Security, and BI teams to ensure AI is built on a sound, governed data foundation and integrates with RCN's enterprise architecture.
• Ensure consistent business definitions and canonical data models to prevent "multiple versions of the truth."
• Evaluate and select data and AI platforms, tools, and vendors-balancing speed of innovation with security, governance, and sustainability.
• Establish reusable patterns for data pipelines, analytics models, and AI enabled applications.
Governance, Risk & Responsible AI
• Define and enforce AI governance standards, including model usage, privacy, security, explainability, and regulatory considerations.
• Ensure compliance with internal policies and external regulations appropriate to financial services.
• Mitigate risks such as hallucinations, bias, uncontrolled automation, or ungoverned model usage.
Organizational Enablement & Change Leadership
• Lead cross functional change by embedding data and AI into real business workflows, not standalone tools.
• Educate executives, managers, and teams on data ownership, governance responsibilities, and AI capabilities.
• Chair or lead enterprise governance forums (e.g., Data & AI Governance Council).
• Act as the internal translator between technical capabilities and business outcomes.
Required Qualifications
Experience
  • 3-5 years of experience across data, analytics, AI, or enterprise technology leadership roles
  • Proven experience implementing data governance as an operating model, not just documentation
  • Demonstrated success delivering AI solutions from strategy through production
  • Experience operating at an executive level in complex or regulated environments

Skills & Expertise
  • Deep understanding of:

  • Data governance, quality, metadata, lineage, and lifecycle management
  • Generative AI, machine learning, and advanced analytics
  • Enterprise data and analytics platforms

  • Strong ability to drive clarity, accountability, and execution in ambiguous environments
  • Executive-level communication and influence skills
  • Pragmatic mindset focused on measurable business impact, not technology for its own sake

Preferred Qualifications
  • Financial services, lending, or regulated industry experience
  • Familiarity with modern cloud-based data and AI platforms
  • Experience standing up a data, AI, or analytics center of excellence
  • Experience partnering with consultants, auditors, or regulators on data and AI initiatives

What Success Looks Like
  • Clearly enforced ownership of RCN's most critical data domains
  • Material improvements in data quality and reduction in downstream remediation
  • AI embedded directly into core operations and decision-making
  • Reduced fragmentation across data and AI initiatives
  • A scalable, governed data and AI foundation that supports long-term growth

Schedule and Work Model:
  • Full-time, Monday-Friday, 9:00 AM - 6:00 PM
  • Hybrid work model: 2 days per week in office
  • First 90 days onsite for training and onboarding

Why RCN Capital:
  • Growth-oriented environment with opportunities to expand your legal skill set
  • Ongoing training and development
  • Casual dress policy
  • Free food and beverage program
  • Competitive benefits, including 401(k)
  • And many additional perks

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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