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Data Integration Jobs in Connecticut (NOW HIRING)

SoTalent

Data Engineer

Shelton, CT · On-site

$114K - $137K/yr

Data Integration Frameworks * Data Services * Enterprise Data Platforms Platform Reliability Ensure data platforms deliver: * High Availability * Scalability * Performance * Reliability * Security ...

Info Dinamica Inc

Data Architect

Hartford, CT · On-site

$64.25 - $82.75/hr

Experience with ETL/ELT frameworks and data integration. Strong SQL skills and experience with relational and NoSQL databases. Experience with Apache Kafka or similar messaging/event streaming ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · On-site

$115K - $138K/yr

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · On-site +1

$115K - $138K/yr

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data ...

Fladger Associates

Scientist III

Ridgefield, CT · On-site

Data Integration: Analyzing diverse datasets (multi-omics) to find relevant drug discovery targets and downstream effects relevant to immune disease * Data Mining: Internal, collaborative, and public ...

The Hartford

AVP, Data Platform Engineering

Hartford, CT · On-site

$115K - $138K/yr

Data Integration & Third-Party Data Enablement * Lead teams responsible for enterprise data ... integration, ingestion, API enablement, Third-Party Data services, and data movement capabilities ...

The Hartford

AVP, Data Platform Engineering

Hartford, CT · On-site

$177K - $266K/yr

Data Integration & Third-Party Data Enablement * Lead teams responsible for enterprise data ... integration, ingestion, API enablement, Third-Party Data services, and data movement capabilities ...

Sonsoft Inc

Big Integrate

Hartford, CT · On-site

Ability to understand DWH / Informatics data integration and processing for Healthcare. * Good Knowledge of Healthcare domain for Member, Product, Plan, Claims and DWH processing. Additional ...

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Data Integration information

See Connecticut salary details

$9

$49

$80

How much do data integration jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for data integration in Connecticut is $49.17, according to ZipRecruiter salary data. Most workers in this role earn between $41.39 and $55.34 per hour, depending on experience, location, and employer.

What is a data integration?

A Data Integration job involves combining data from different sources into a unified view for analysis, reporting, and operational use. Professionals in this role design, develop, and maintain data pipelines to ensure seamless data flow between systems. They often work with ETL (Extract, Transform, Load) processes, APIs, and cloud platforms to facilitate integration. Strong skills in SQL, data modeling, and tools like Informatica, Talend, or Apache Nifi are commonly required. Their goal is to ensure data accuracy, consistency, and availability for business and analytical use.

What are the typical daily responsibilities of someone working in data integration?

Data Integration professionals are often responsible for designing, developing, and maintaining ETL pipelines that transfer and transform data between different systems. Their day-to-day tasks may include analyzing data sources, troubleshooting data inconsistencies, optimizing integration workflows, and creating documentation for data processes. Collaboration is frequent, as they work closely with database administrators, data analysts, and business stakeholders to ensure data accuracy and availability. Staying updated with evolving tools and best practices also forms a key part of their ongoing responsibilities.

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

To thrive as a Data Integration professional, you need strong knowledge of data management principles, proficiency in SQL, ETL processes, and experience with data warehousing concepts, often supported by a bachelor's degree in computer science or a related field. Familiarity with integration platforms such as Informatica, Talend, or Microsoft SSIS, as well as certifications like Certified Data Management Professional (CDMP), are commonly beneficial. Excellent problem-solving, communication, and collaboration skills help manage complex projects and liaise with stakeholders across technical and business teams. These abilities are crucial for ensuring seamless, accurate data flow that supports informed business decisions and operational efficiency.

How to become a data integration specialist?

To become a data integration specialist, you typically need a bachelor's degree in computer science, information technology, or a related field. Gaining experience with data management, ETL tools, and programming languages like SQL, Python, or Java is essential, along with knowledge of database systems and data warehousing. Certifications such as Certified Data Management Professional (CDMP) or vendor-specific credentials can enhance job prospects.

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

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

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

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

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

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

Data Integration jobs near you
Infographic showing various Data Integration job openings in Connecticut as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 79% Full Time, 12% Part Time, 1% Temporary, and 6% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $102,264 per year, or $49.2 per hour.

Data Engineer

Shelton, CT • On-site

SoTalent
See more jobs at SoTalentexternal

$114K - $137K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Data Engineer

📍 Location: Shelton, CT, United States

🏢 Industry: Restaurants

💼 Work Setting: Hybrid


Are you a data engineering leader with experience building modern cloud-based data platforms, leading high-performing teams, and enabling analytics and data-driven decision making? This role offers the opportunity to shape the organization's data engineering roadmap, modernize data platforms, improve data reliability, and support enterprise analytics, BI, AI, and data products.

As the Director of Data Engineering, you will partner closely with Data Product, Analytics, Enterprise Architecture, Platform Engineering, Security, and Compliance teams to ensure trusted, scalable, and accessible data solutions across the organization.


Key Responsibilities

Data Engineering Strategy & Leadership

Data Roadmap Ownership

  • Own and execute the enterprise data engineering roadmap.
  • Align engineering priorities with business and data product objectives.
  • Define long-term strategies for data platform modernization and scalability.
  • Drive adoption of modern data engineering best practices.

Organizational Leadership

  • Lead and develop managers, technical leads, and senior data engineers.
  • Build a high-performing engineering culture focused on reliability, ownership, and innovation.
  • Drive hiring, coaching, succession planning, and career development.

Data Platform Architecture & Delivery

Data Pipeline Engineering

Design, build, and support scalable:

  • Batch Processing Pipelines
  • Streaming Data Pipelines
  • Data Integration Frameworks
  • Data Services
  • Enterprise Data Platforms

Platform Reliability

Ensure data platforms deliver:

  • High Availability
  • Scalability
  • Performance
  • Reliability
  • Security

Data Lifecycle Management

Oversee:

  • Data Ingestion
  • Data Transformation
  • Data Processing
  • Data Delivery
  • Data Consumption

Data Platform Modernization

Technology Transformation

  • Drive modernization initiatives across data ecosystems.
  • Reduce technical debt and improve maintainability.
  • Evaluate and implement emerging technologies and frameworks.
  • Improve operational efficiency and platform scalability.

Enterprise Standards

  • Establish reusable engineering frameworks and patterns.
  • Promote consistency and standardization across teams.
  • Align engineering practices with enterprise architecture principles.

Data Quality, Governance & Observability

Data Quality Management

  • Establish standards for enterprise data quality.
  • Monitor data accuracy, completeness, and consistency.
  • Improve trust in organizational data assets.

Observability & Monitoring

Develop standards for:

  • Data Observability
  • Monitoring
  • Alerting
  • Incident Response
  • Root Cause Analysis

Lineage & Documentation

  • Ensure traceability of critical data assets.
  • Implement documentation standards.
  • Enable transparency across data pipelines and platforms.

Cross-Functional Collaboration

Business & Product Alignment

Partner with:

  • Data Product Managers
  • Analytics Teams
  • BI Teams
  • Data Scientists
  • Enterprise Architects
  • Platform Engineering Teams

Outcome-Focused Delivery

  • Translate business goals into engineering priorities.
  • Deliver trusted datasets that support strategic decision-making.
  • Enable self-service analytics and advanced data capabilities.

Security, Privacy & Compliance

Data Protection

Collaborate with:

  • Security Teams
  • Privacy Officers
  • Compliance Organizations

To ensure:

  • Data Security
  • Regulatory Compliance
  • Access Controls
  • Data Governance Standards

Risk Management

  • Implement secure data engineering practices.
  • Ensure adherence to enterprise compliance requirements.
  • Support audit and regulatory initiatives.

Performance & Operational Excellence

KPI Management

Define and monitor metrics such as:

  • Pipeline Reliability
  • Data Freshness
  • Data Availability
  • SLA Performance
  • Cost Efficiency
  • Platform Utilization

Service Delivery

  • Establish operational excellence standards.
  • Improve platform stability and resiliency.
  • Drive continuous improvement initiatives.


Required Qualifications

Education

Bachelor's Degree in:

  • Computer Science
  • Engineering
  • Data Science
  • Information Technology
  • Related Technical Field

Preferred

  • Master's Degree or Advanced Technical Degree

Experience

Data Engineering

  • 8-12 years of experience in:
  • Data Engineering
  • Data Platforms
  • Cloud Data Infrastructure
  • Analytics Engineering

Leadership

  • 3-5 years of experience leading teams, managers, or enterprise-scale data engineering functions.
  • Proven success managing large technical organizations.

Enterprise Data Platforms

Strong experience with:

  • Cloud Data Platforms
  • Distributed Systems
  • Enterprise Data Architectures
  • Large-Scale Data Processing


Technical Skills

Data Engineering

  • Data Pipelines
  • ETL / ELT
  • Batch Processing
  • Streaming Architectures
  • Data Integration

Cloud Technologies

  • Cloud Data Platforms
  • Distributed Computing
  • Enterprise Data Ecosystems
  • Data Platform Operations

Architecture & Governance

  • Data Modeling
  • Data Governance
  • Data Quality
  • Data Lineage
  • Data Observability

Analytics Enablement

  • Business Intelligence
  • Analytics Platforms
  • Data Warehousing
  • Data Science Enablement


Key Skills

  • Data Engineering Leadership
  • Data Platform Strategy
  • Cloud Data Platforms
  • Data Architecture
  • ETL/ELT
  • Data Pipelines
  • Streaming Data
  • Data Governance
  • Data Quality
  • Platform Modernization
  • Analytics Enablement
  • Team Leadership

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