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Contract Data Management Jobs in Connecticut (NOW HIRING)

USM

Sr. Data Analyst

Windsor, CT

$45 - $50/hr

... M counselling, Product Engineering, Business Intelligence, Data Management, SOA, BPM, Data ... Contract Duration: 6+ months Location: Windsor, CT Rate: $45-50/hr on C2C or 1099 and $44/hr on W2 ...

Actalent

Clinical Data Coordinator

New Haven, CT

$28 - $31.83/hr

The coordinator will provide direct clinical and data management support related to the conduct of ... Job Type & Location This is a Contract to Hire position based out of New Haven, CT. Pay and ...

Integrated Resources INC

Contract Manager

Bridgeport, CT

$90K - $121K/yr

Participate and contribute "cradle to grave" contract management from early involvement with ... Analyze data to support contractor/vendor evaluation Establish/measure/analyze contractor ...

GameChange Energy

Contract Manager

Norwalk, CT · On-site

$65K - $70K/yr

Enter, update, and track contract and supplier documentation and ensure key data, status, and ... Coordinate with Legal, Finance, Business Development, Project Management, Logistics and Operations ...

GameChange Solar Corp

Contracts Manager

Norwalk, CT · On-site

$65K - $70K/yr

Enter, update, and track contract and supplier documentation and ensure key data, status, and ... Coordinate with Legal, Finance, Business Development, Project Management, Logistics and Operations ...

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All JobsContract Data Management JobsContract Data Management Jobs in Connecticut

Contract Data Management information

See Connecticut salary details

$29.5K

$92.4K

$163.6K

How much do contract data management jobs pay per year?

As of Aug 21, 2026, the average yearly pay for contract 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 contract data management?

Contract data management refers to the process of organizing, storing, tracking, and analyzing data related to contracts within an organization. This involves managing all contract documents, key dates, obligations, compliance requirements, and performance metrics to ensure that contractual agreements are properly executed and monitored. Effective contract data management helps reduce risk, improve compliance, and optimize business relationships by providing easy access to contract information and supporting informed decision-making.

What are some common challenges faced by professionals in contract data management, and how can they be addressed?

Professionals in Contract Data Management often encounter challenges such as handling large volumes of contracts, ensuring data accuracy, and maintaining compliance with regulatory requirements. Managing multiple contract versions and tracking key dates or obligations can also be complex. These challenges can be mitigated by using robust contract management software, establishing standardized processes for data entry and review, and fostering strong communication with legal, procurement, and business teams. Regular training and clear documentation also help ensure data integrity and operational efficiency.

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

Excelling in Contract Data Management requires strong analytical abilities, attention to detail, and a background in business administration, law, or a related field. Familiarity with contract lifecycle management (CLM) software, databases, and proficiency in tools like Microsoft Excel are typically necessary, with certifications such as CFCM (Certified Federal Contracts Manager) being advantageous. Exceptional organizational skills, effective communication, and problem-solving abilities help professionals manage complex contract data and collaborate with stakeholders. These skills ensure accurate data management, mitigate risks, and support compliance with legal and organizational requirements.

What is the difference between Contract Data Management vs Contract Analyst?

AspectContract Data ManagementContract Analyst
Primary FocusManaging and organizing contract data, ensuring data accuracy and accessibilityAnalyzing contract terms, financials, and compliance
Skills & CertificationsData management, database tools, attention to detailContract law, financial analysis, negotiation skills
Work EnvironmentAdministrative, data-driven roles within procurement or legal teamsContract review, negotiation, and analysis in legal or procurement departments

Contract Data Management focuses on organizing and maintaining contract information, while Contract Analysts analyze contract details to support decision-making. Both roles are essential in contract lifecycle management but serve different functions within organizations.

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 cities in Connecticut are hiring for Contract Data Management jobs?

Cities in Connecticut with the most Contract Data Management job openings:

Contract Data Management jobs near you
Infographic showing various Contract Data Management job openings in Connecticut as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person 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 3 days ago

New

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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