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Data Systems Manager Jobs in Granby, CT (NOW HIRING)

Kemper

Senior Data Systems Analyst

Hartford, CT

Production Incident and Problem Management * Investigate production data incidents and quality ... Validate system behavior under expected and peak business workloads. * Assess data processing ...

ebm-papst Inc.

Quality Systems Manager

Farmington, CT · On-site

$115K/yr

Review data obtained during quality control and quality assurance activities to ensure consistency ... MAC-PAC, Order Processing, Inventory Systems, Design, Internet, Project Management, Microsoft Word ...

The Hartford

Lead Staff AI Data Engineer

Hartford, CT · On-site +1

Develop AI-driven data systems that enhance data capabilities while ensuring adherence to industry ... Experience working across teams with strong communication and stakeholder management skills

Webster Bank

Manager, Financial Analytics

Waterbury, CT

$107K - $141K/yr

Develop expert knowledge and experience with Webster's data systems and tools. * Develop strong ... Proven ability to manage multiple priorities, meet deadlines, and adapt to changing business needs ...

Webster Bank

Manager, Financial Analytics

Southington, CT

$107K - $140K/yr

Develop expert knowledge and experience with Webster's data systems and tools. * Develop strong ... Proven ability to manage multiple priorities, meet deadlines, and adapt to changing business needs ...

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All JobsData Systems JobsData Systems Manager JobsData Systems Manager Jobs in Granby, CT

Data Systems Manager information

See Granby, CT salary details

$47.1K

$114.8K

$201.9K

How much do data systems manager jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data systems manager in Granby, CT is $114,780.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,300.00 and $139,400.00 per year, depending on experience, location, and employer.

What is a data systems manager?

Data Systems Managers are professionals responsible for overseeing the design, implementation, and maintenance of an organization's data management systems. They ensure that data storage, retrieval, and security processes run smoothly, supporting business operations and decision-making. Typically, they manage teams of IT specialists, coordinate with other departments, and stay updated with evolving technologies. Their role is critical for ensuring the accuracy, accessibility, and security of organizational data.

What are the key skills and qualifications needed to thrive as a data systems manager?

To excel as a Data Systems Manager, you need expertise in database management, data architecture, and systems integration, often supported by a degree in information technology or computer science. Familiarity with SQL, cloud platforms (such as AWS or Azure), and certifications like Certified Data Management Professional (CDMP) are highly valuable. Strong leadership, problem-solving abilities, and effective communication distinguish top performers in this role. These competencies ensure that data systems are secure, efficient, and aligned with organizational goals, enabling informed decision-making.

What are some common challenges faced by data systems managers when integrating new technologies into existing data infrastructure?

Data Systems Managers often encounter challenges such as ensuring compatibility between legacy systems and new technologies, minimizing downtime during migration, and maintaining data integrity throughout the integration process. They also need to coordinate closely with IT, security, and business teams to align technology upgrades with organizational goals and compliance requirements. Effective change management and thorough testing are crucial to address these challenges and ensure a smooth transition.

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

AspectData Systems ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like Cisco, Microsoft, or cloud certificationsBachelor's degree in Statistics, Mathematics, or related field; certifications like Microsoft Excel, Tableau, or SQL
Work EnvironmentIT departments, data management teams, enterprise environmentsBusiness units, marketing, finance, data visualization teams
Employer & Industry UsageTech companies, large corporations, government agenciesMarketing firms, finance companies, consulting agencies

The Data Systems Manager oversees data infrastructure, ensuring systems run efficiently, while the Data Analyst interprets data to provide insights. Both roles require technical skills, but the manager focuses on system management, whereas the analyst emphasizes data analysis and reporting.

What cities near Granby, CT are hiring for Data Systems Manager jobs?

Cities near Granby, CT with the most Data Systems Manager job openings:

Data Systems Manager jobs near you
Infographic showing various Data Systems Manager job openings in Granby, CT as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 4% Contract, and 1% Nights. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $114,780 per year, or $55.2 per hour.

Senior Data Systems Analyst

Kemper

Hartford, CT

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

Location(s)

Bloomington, Illinois, Boston, Massachusetts, Hartford, Connecticut, Omaha, Nebraska, P&C-Butterfield Road-Downers Grove-IL-AAC, San Antonio, Texas

Details

Kemper is one of the nation's leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture, valuable opportunities for personal development and professional challenge, and a healthy work-life balance can be highly motivating and productive. Kemper's products and services are making a real difference to our customers, who have unique and evolving needs. By joining our team, you are helping to provide an experience to our stakeholders that delivers on our promises.

Position Summary:

Kemper is seeking a highly analytical and detail-oriented Data Systems Analyst to provide independent validation and quality assurance across enterprise data platforms, business processes, and reporting solutions. This role is responsible for ensuring the accuracy, completeness, reliability, and regulatory compliance of critical business data and end-to-end data workflows.

The Data Systems Analyst serves as an independent quality function within the Data Engineering organization, partnering closely with business stakeholders, data engineers, data architects, product owners, compliance teams, and operational teams to validate business requirements, identify data quality risks, and ensure enterprise data solutions meet business and regulatory expectations.

The ideal candidate possesses strong expertise in data analysis, data warehousing, systems analysis, business process validation, testing methodologies, and data governance. This individual will independently assess data quality across source systems, transformations, integrations, reporting platforms, and downstream consumers while driving continuous improvement in enterprise data quality practices.

Position Responsibilities:

Production Incident and Problem Management

  • Investigate production data incidents and quality issues.
  • Perform root cause analysis and identify corrective and preventive actions.
  • Partner with engineering and operational teams to prioritize remediation activities.
  • Track recurring issues and recommend long-term quality improvements.

Test Strategy and Quality Assurance

  • Develop and maintain comprehensive testing strategies for enterprise data platforms and business-critical processes.
  • Create test cases, test scenarios, traceability matrices, and validation documentation.
  • Establish risk-based testing approaches to ensure appropriate coverage of critical business functions.
  • Define quality gates and acceptance criteria for data products and platform releases.

Test Automation and Quality Frameworks

  • Collaborate with data engineering teams to develop reusable testing assets and automated validation processes.
  • Support implementation of automated testing frameworks for data validation, reconciliation, regression testing, and quality monitoring.
  • Promote quality engineering best practices across the data organization.

Regression and Release Validation

  • Conduct regression testing across enterprise systems following enhancements, migrations, platform upgrades, and releases.
  • Assess downstream impacts of system and data changes.
  • Validate production deployments and release readiness.

Non-Functional Testing

  • Support performance, scalability, reliability, recoverability, and operational readiness testing.
  • Validate system behavior under expected and peak business workloads.
  • Assess data processing performance and service-level requirements.

End-to-End Data Workflow Testing

  • Design and execute test plans for complex business and data workflows spanning multiple applications, databases, integrations, and reporting platforms.
  • Validate data movement across source systems, ETL/ELT processes, data warehouses, reporting environments, and downstream consumers.
  • Perform system integration testing, user acceptance testing support, and production validation activities.

Business Requirements Analysis

  • Partner with business stakeholders, product owners, and data engineering teams to clarify and refine requirements.
  • Translate business requirements into testable scenarios and validation criteria.
  • Challenge assumptions and identify requirement gaps, ambiguities, and potential quality risks early in the delivery lifecycle.

Data Quality Governance and Metrics

  • Develop and monitor data quality KPIs, controls, and scorecards.
  • Support enterprise data quality governance initiatives.
  • Contribute to the establishment of data quality standards, policies, and operating procedures.
  • Drive continuous improvement of data quality management practices.

Independent Business Process Validation

  • Independently validate critical business processes and supporting data workflows across operational, analytical, and regulatory systems.
  • Evaluate end-to-end business process execution to ensure data integrity, accuracy, completeness, and consistency throughout the data lifecycle.
  • Identify control gaps, data risks, process deficiencies, and opportunities for quality improvement.

Data Quality Analysis and Validation

  • Perform independent validation of enterprise data assets, reports, dashboards, and regulatory submissions.
  • Conduct data profiling, reconciliation, root cause analysis, and quality assessments across structured and semi-structured data.
  • Validate business rules, transformations, calculations, aggregations, and reporting logic.
  • Analyze data anomalies, trends, and quality metrics to identify potential issues and risks.

Governance, Compliance, and Regulatory Validation

  • Ensure compliance with enterprise data governance standards, policies, and controls.
  • Validate regulatory, audit, financial, operational, and compliance-related data requirements.
  • Support internal and external audit activities through independent quality assessments and evidence collection.
  • Verify adherence to data lineage, data retention, privacy, and security requirements.

Collaboration and Leadership

  • Serve as a trusted advisor on data quality and validation practices.
  • Collaborate across business, technology, risk, compliance, and operational teams.
  • Mentor junior analysts and promote quality-focused thinking across the organization.
  • Champion a culture of quality, accountability, and continuous improvement.

Position Qualifications:

Required Skills and Experience

  • Bachelor's degree in Information Systems, Computer Science, Data Analytics, Business Analytics, or a related field; equivalent work experience considered.
  • 6+ years of experience in one or more of the following areas:
    • Data Quality Analysis
    • Data Warehousing
    • Business Systems Analysis
    • Data Governance
    • Quality Assurance
    • Data Testing
    • Business Process Validation
  • Insurance industry experience (P&C and/or Life Insurance).
  • Experience supporting enterprise data warehouse environments.

Demonstrated Expertise In

  • Data quality management principles and methodologies
  • End-to-end business process testing
  • Data warehouse validation and reporting verification
  • Data reconciliation and data profiling techniques
  • SQL querying and data analysis
  • Root cause analysis and problem-solving methodologies
  • Test planning, test design, and test execution
  • Regression testing and release validation
  • Requirements analysis and requirements traceability
  • Data governance and data stewardship practices
  • Regulatory, compliance, and audit-related data validation
  • Production incident investigation and resolution support
  • Data lineage, metadata, and data quality controls
  • Relational database concepts and data modeling
  • Validation of ETL/ELT processes and enterprise data pipelines

Technical Skills

  • Advanced SQL development and data analysis
  • Experience working with Snowflake, Oracle, SQL Server, or similar database platforms
  • Familiarity with Informatica, IICS, or enterprise data integration platforms
  • Experience using reporting and analytics tools such as Power BI
  • Experience working with XML, JSON, and API-based integrations
  • Familiarity with Python or other scripting languages for data analysis and automation
  • Experience with Azure, AWS, or cloud-based data platforms

Professional Competencies

  • Strong analytical and critical thinking skills
  • Excellent communication and stakeholder management abilities
  • Ability to work independently with minimal supervision
  • Strong documentation and organizational skills
  • High attention to detail and commitment to data accuracy
  • Ability to manage multiple priorities in a fast-paced environment
  • Strong intellectual curiosity and continuous improvement mindset

Preferred Qualifications

  • Experience with data quality, observability, or governance tools.
  • Familiarity with CI/CD practices and automated testing frameworks.
  • Experience with DataOps, DevOps, or Agile delivery methodologies.
  • Exposure to large-scale cloud data platforms and distributed data ecosystems.
  • Experience with AI-assisted testing, validation, and data quality monitoring tools.
  • Knowledge of data lineage, metadata management, and master data management concepts.
  • Experience supporting enterprise audit and regulatory compliance initiatives.
  • The position can be worked hybrid out of a local Kemper office or remotely for a non-local candidate.

The range for this position is $89,000 to $148,100. Whendeterminingcandidate offers, we consider experience, skills, education, certifications, and geographic location among other factors. This job is eligible for an annual discretionary bonus and Kemper benefits (Medical, Dental, Vision, PTO, 401k, etc.)

Kemper is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other status protected by the laws or regulations in the locations where we operate. We are committed to supporting diversity and equality across our organization and we work diligently to maintain a workplace free from discrimination.

Kemper does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Kemper and Kemper will not be obligated to pay a placement fee.

Kemper will never request personal information, such as your social security number or banking information, via text or email.Additionally, Kemper does not use external messaging applications like WireApp or Skype to communicate with candidates.If you receive such a message, delete it.

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