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Data Management Jobs in Connecticut (NOW HIRING)

Collabera

Data Analyst

Hartford, CT · On-site

Reviews, enhances and tests data management processes. Performs data and process analysis. Ability to write SQL code in multiple OS platforms & software. Qualifications Qualifications: Competent in ...

Bridgewater Associates

Data Associate

Westport, CT · On-site

About Bridgewater Bridgewater Associates is a premier asset management firm, focused on delivering ... About Your Role As a Data Associate, you will help us achieve our mission by owning and deeply ...

Sun Life Financial

Director, Data Science

Hartford, CT · On-site

Manage and develop a team of data scientists, balancing team development, delivery priorities, and ... long-term capability building. * Monitor solution performance, user feedback, data quality, model ...

Chubb

Head of Data, North America

Simsbury, CT · On-site

The leader is also tasked with the management and long-term prioritization of the business's overall data priorities needs and opportunities. The role will encompass building and sharing our North ...

Chubb

Head of Data, North America

Simsbury, CT · On-site

The leader is also tasked with the management and long-term prioritization of the business's overall data priorities needs and opportunities. The role will encompass building and sharing our North ...

Chubb

Head of Data Products, PRS

Simsbury, CT · On-site

$224K - $314K/yr

Advance data governance and master/reference data management as a strategic discipline. * Implement strategies to monitor the effectiveness of data engineering. * Mentor/Train Engineers within the ...

Chubb

Head of Data Products, PRS

Simsbury, CT · On-site

Advance data governance and master/reference data management as a strategic discipline. * Implement strategies to monitor the effectiveness of data engineering. * Mentor/Train Engineers within the ...

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Showing results 21-40

All JobsData Management JobsData Management Jobs in Connecticut

Data Management information

See Connecticut salary details

$29.5K

$92.4K

$163.6K

How much do data management jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data management in Connecticut is $92,412.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,800.00 and $119,400.00 per year, depending on experience, location, and employer.

What is data management?

Data management is the process of collecting, storing, organizing, and maintaining data in a secure and efficient manner. It ensures that data is accurate, available, and accessible to authorized users when needed. Good data management practices help organizations make informed decisions, comply with regulations, and protect sensitive information. It often involves the use of specialized software, policies, and procedures to handle data throughout its lifecycle.

What is a data management analyst?

A data management analyst is responsible for maintaining databases. In this position, your responsibilities are to keep an eye on how secure the data is and look for ways to increase user efficiency when accessing it. For example, you might move the database to an online cloud-based server to free up system resources. A data management analyst has to have a solid grasp of network technology, in addition to familiarity with database and spreadsheet software, to perform the duties of the job.

What are the key skills and qualifications needed to thrive in data management, and why are they important?

To excel in Data Management, you need a strong background in data analysis, database design, and data governance, often supported by a degree in computer science or information systems. Familiarity with database management systems (like SQL, Oracle), data visualization tools, and certifications such as Certified Data Management Professional (CDMP) are highly valued. Attention to detail, problem-solving, and strong organizational skills help professionals ensure data integrity and facilitate effective collaboration. These competencies are crucial for maintaining accurate, secure, and accessible data, which underpins informed business decision-making.

What are some common challenges faced by data management professionals in ensuring data quality and consistency across departments?

Data Management professionals often encounter challenges such as inconsistent data entry practices, siloed information systems, and varying data standards across departments. Addressing these issues typically involves implementing data governance frameworks, standardizing processes, and fostering collaboration between teams to ensure data integrity. Regular audits, cross-functional meetings, and the use of data quality tools are common strategies employed to maintain high standards and support organizational decision-making.

What is the difference between Data Management vs Data Analyst?

AspectData ManagementData Analyst
Primary FocusOrganizing, storing, and maintaining data integrityAnalyzing data to extract insights and support decision-making
Skills & CertificationsDatabase management, SQL, data governance certificationsStatistical analysis, Excel, data visualization tools
Work EnvironmentData warehouses, IT departments, enterprise systemsBusiness units, analytics teams, consulting firms
Industry UsageUsed across industries for data infrastructureUsed for reporting, forecasting, and strategic analysis

While Data Management focuses on maintaining and organizing data infrastructure, Data Analysts interpret this data to generate insights. Both roles are essential for effective data-driven decision-making but serve different functions within an organization.

What is data management as a job?

Data management as a job involves organizing, storing, and maintaining data to ensure its accuracy, security, and accessibility. Professionals in this field often work with database systems, data governance policies, and data quality tools, requiring skills in data analysis, SQL, and sometimes certifications like CDMP or DAMA-DMBOK. The role supports organizations in making informed decisions and complying with data regulations.

What skills are needed for data management jobs?

Data management jobs require strong analytical skills, proficiency in database tools like SQL, data modeling, and knowledge of data governance and security practices. Familiarity with data management software, attention to detail, and the ability to organize large datasets are also essential. Certifications such as Certified Data Management Professional (CDMP) can enhance job prospects.
More about Data Management jobs

What are the most commonly searched types of Data Management jobs in Connecticut?

The most popular types of Data Management jobs in Connecticut are:

What are popular job titles related to Data Management jobs in Connecticut?

For Data Management jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Data Management jobs in Connecticut look for?

The top searched job categories for Data Management jobs in Connecticut are:

What cities in Connecticut are hiring for Data Management jobs?

Cities in Connecticut with the most Data Management job openings:

Data Management jobs near you
Infographic showing various Data Management job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $92,412 per year, or $44.4 per hour.

Director, Product Management - Data Intelligence Foundation (Bridgeport)

Relativity

Bridgeport, CT • On-site

Full-time

Posted 19 days ago

Job description

Remote/Hybrid

Job Overview

Relativity is a leading legal data intelligence company building AI technology that helps organizations organize data, discover the truth, and act on it with confidence. Over two decades, the company has built the most trusted platform in legal data, earning deep relationships with the world's leading law firms, corporations, and government agencies, and managing petabytes of the most sensitive data in existence. That foundation is now being turned into something larger: The AI platform for legal data intelligence. The Relativity Intelligence Model is the architecture for that transformation. At its base is the Foundational Layer (Relativity's shared data platform serving all AI applications). Five primitives give AI agents the structure, meaning, and retrieval capability they need to reason over legal data at scale: Files, Ontology, Data Capabilities, Knowledge/Metadata, and Query Plane. Relativity's Data Intelligence Foundation engineering org is building this layer. The product leadership that shapes it, drives adoption across Relativity's product teams, and builds the PM discipline to own it long-term. That's this role. The Director of Product Management, Data Intelligence Foundation is one of the highest-leverage product roles at Relativity. The Foundational Layer is what makes every Relativity aiR application smarter, every agent more reliable, and every Relativity product team faster. Getting it right matters enormously.

Job Description and RequirementsWhat you’ll ownThe full PM layer across multiple engineering orgs

  • Files / Natives: The storage primitive for legal documents, images, and native files. You define the substrate that makes immutable legal data consistently accessible across every product, partner integration, and AI workflow, with the SLAs, access contracts, and API surface that teams can build on with confidence. The underlying data primitives are the foundation; the degree to which the retrieval layer (Query Plane) matches this structure determines how easily the organization can navigate between slow data and fast data use cases.

  • Ontology / Relationship: The semantic layer of the Relativity Intelligence Model. Ontology encodes meaning: what kinds of things exist in legal data and how they relate, so that AI agents can reason, not just query. You define what Relativity's Ontology becomes: the entities, relationships, and contracts that give every Skill and Agent a shared vocabulary for legal data.

  • Data Capabilities: Reporting, Audit, and internal data infrastructure. The operational backbone that makes the platform observable, auditable, and explainable. These are non-negotiable properties in legal data intelligence use cases.

  • Knowledge / Metadata: The core data model that every product team, customer, and integration partner works with. A unified materialized document layer, consistent across all workspaces, is the mandate. Your roadmap evolves this surface to serve AI application teams as first-class consumers alongside the users who have relied on it for years.

  • Query Plane: One of the most performance-sensitive and strategically important services in the product. The mandate is a unified retrieval pillar with a rich materialized document layer: standardized ingestion APIs independent of data source, hybrid retrieval (lexical + vector) with reranking, chunking as a managed capability, and tiered storage (cold/warm/hot).

Minimum qualifications

  • 12+ years in product management; 5+ years leading platform or infrastructure PM organizations

  • Deep fluency with data platform primitives, including storage systems, metadata layers, knowledge graphs, query engines, or equivalent. You can design an

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