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Data Integration Engineer Jobs (NOW HIRING)

DATA INTEGRATION ENGINEER

Worcester, MA ยท Hybrid

$114.10K - $137K/yr

Data Integration Engineer Location: Hybrid in Worcester, MA 3days/week (Local or from nearby states who can relocate on day 1) Duration: 6+ months CTH MoI: 2 Video and F2F for local or within ...

The Senior Data Integration Engineer is responsible for extracting and integrating data from SCN BestCo's core systems, including SAP, JD Edwards (JDE), AMAPS, and other enterprise applications, into ...

... data engineering projects simultaneously. Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation required to ...

... data engineering projects simultaneously. Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation required to ...

Integration (Data) Engineer Location: Mexico Duration: 3+ months About Job: We are seeking a talented Integration Engineer with a strong background in data integration, ETL (Extract, Transform, Load ...

Data Integration Engineer

San Antonio, TX ยท On-site

$103.30K - $124K/yr

The Data Integration Engineer will own the design, build, and operation of scalable data pipelines and warehouse models that power analytics and operational reporting. You'll integrate diverse ...

Data Integration Engineer

Sunnyvale, CA

$136.20K - $163.60K/yr

... data marketplace integrations o Engineer Snowpipe and Kafka-to-Snowflake streaming ingestion pipelines also handling high throughput event data at scale o Optimize Snowflake cluster performance ...

Data Integration Engineer

San Antonio, TX ยท On-site

$103.30K - $124K/yr

The Data Integration Engineer will own the design, build, and operation of scalable data pipelines and warehouse models that power analytics and operational reporting. You'll integrate diverse ...

SCN BestCo is a leading innovator in the Vitamin, Mineral & Supplement industry, seeking a Senior Data Integration Engineer to enhance their data management capabilities. The role involves extracting ...

Data Integration Engineer

San Antonio, TX ยท On-site

$103.30K - $124K/yr

The Data Integration Engineer will own the design, build, and operation of scalable data pipelines and warehouse models that power analytics and operational reporting. Youll integrate diverse sources ...

Data Integration Engineer

Austin, TX ยท On-site

$113.50K - $136.30K/yr

SourceDay needs someone who has the experience in developing data integrations of third-party ... If you answered yes to all of these then you will enjoy being a part of the SourceDay's engineering ...

Data Integration Engineer

Austin, TX ยท On-site

$113.50K - $136.30K/yr

SourceDay needs someone who has the experience in developing data integrations of third-party ... If you answered yes to all of these then you will enjoy being a part of the SourceDay's engineering ...

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Data Integration Engineer information

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$10

$51

$84

How much do data integration engineer jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for data integration engineer in the United States is $51.68, according to ZipRecruiter salary data. Most workers in this role earn between $43.51 and $58.17 per hour, depending on experience, location, and employer.

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

To thrive as a Data Integration Engineer, you need strong skills in data modeling, ETL (extract, transform, load) processes, and experience with database management, often supported by a degree in computer science or a related field. Familiarity with integration tools like Informatica, Talend, or Microsoft SSIS, and knowledge of programming languages such as SQL and Python, are typically required. Excellent problem-solving abilities, attention to detail, and effective communication help you collaborate with cross-functional teams and resolve integration challenges. These skills are critical for ensuring seamless data flow, system interoperability, and the delivery of reliable, actionable business insights.

What are some common challenges Data Integration Engineers face when working with multiple data sources?

Data Integration Engineers often encounter challenges such as handling inconsistent data formats, resolving data quality issues, and ensuring seamless data flow between disparate systems. Integrating legacy databases with modern cloud platforms can require creative problem-solving and careful planning. Additionally, maintaining data security and compliance across various sources demands a strong understanding of protocols and best practices. Collaboration with data architects, developers, and business analysts is crucial to address these challenges effectively and deliver reliable integration solutions.

What are Data Integration Engineers?

Data Integration Engineers are IT professionals who design, build, and maintain systems that combine data from multiple sources into a unified view. They develop and manage data pipelines, ensuring data flows smoothly between databases, applications, and storage solutions. Their work enables organizations to access accurate and consistent information for analytics, reporting, and business decision-making. Data Integration Engineers often use ETL (Extract, Transform, Load) tools, APIs, and custom scripts to achieve seamless data integration.

What is the difference between Data Integration Engineer vs Data Engineer?

AspectData Integration EngineerData Engineer
Primary FocusDesigning and implementing data pipelines for integration and ETL processesBuilding and maintaining data infrastructure, including storage and processing systems
Skills & CertificationsSQL, ETL tools, data warehousing, cloud platformsSQL, programming (Python, Java), big data technologies, cloud services
Work EnvironmentData teams, analytics departments, data warehousesData engineering teams, infrastructure, data lakes
Industry UsageUsed across industries for data integration tasksUsed for creating scalable data pipelines and infrastructure

While both roles involve working with data, Data Integration Engineers focus on connecting and transforming data from various sources, whereas Data Engineers build the underlying systems and infrastructure to support data storage and processing. Both roles often collaborate but serve different core functions within data teams.

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What job categories do people searching Data Integration Engineer jobs look for? The top searched job categories for Data Integration Engineer jobs are:
DATA INTEGRATION ENGINEER

DATA INTEGRATION ENGINEER

InterSources

Worcester, MA โ€ข Hybrid

$114.10K - $137K/yr

Other

Posted 6 days ago


Job description

Data Integration Engineer

Location: Hybrid in Worcester, MA 3days/week (Local or from nearby states who can relocate on day 1) Duration: 6+ months CTH MoI: 2 Video and F2F for local or within drivable distance candidates

Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. This role will primarily become proficient with all internal & external data produced and consumed by THG. The engineer will understand where the data is, basic data models and architecture, how to access and obtain data, and how to manipulate and work with data to produce output, which may be reports, datasets, or self-service reports. The ideal candidate is a self-motivated, adaptable, and composed collaborator who can learn quickly.

Responsibilities & Essential Functions

This role will be driving larger, more complicated projects independently, as well as mentoring less experienced engineers. Data Engineer will collaborate with business partners and cross-functional teams on data/reporting requests. The assignments will become broader in nature, usually requiring originality and ingenuity. This role will be accountable for successful outcomes related to designing, developing, implementing, optimizing, and maintaining data integrations, pipelines, and solutions.

Skills, Experience, and Qualifications

Skills: Mandatory: Java, JDBC Template, JPA, Springboot, Ehcache, SQL, REST. Proficiency in the following languages: Java, SQL, Python, and Scala (prioritized order). Data Modeling: Creation of conceptual, logical, and physical data models for data objects, object attributes, and their relationships. Analytical Skills: Data Engineers work with large amounts of data that will include facts, figures, and number crunching. You will need to profile the data and analyze it to find conclusions. Communication Skills: Data engineers are often called to present their findings or translate the data into an understandable document. You will need to write and speak clearly, easily communicating complex ideas. Critical Thinking: Data engineers must look at the numbers, trends, and data and come to new conclusions based on the findings. Attention to Detail: Data engineers must make sure they are vigilant in their analysis to come to correct conclusions. Math Skills: Data engineers need advanced math skills to estimate numerical data. Insurance experience required, as well as insurance products. Debugging Skills: Data engineers need the ability to analyze issues with components in our data solutions and come up with remediation plans.

Experience: Experience in Java development with Java 8 & above, J2EE, Hibernate, Maven, GiT, Jenkins, JSON frameworks, XML, JMS, JDBC, Junit-based testing frameworks like Mockito. Demonstrated proficiency in Spring Framework, including Data (JDBC, ORM, JMS), Security &Integration. Proven experience in data engineering, implementation of best practices for data storage, integration, transformation, access, etc., within Azure and on-premise platforms. Experience in building and optimizing real-time and near-real-time data integration solutions for scale, performance, reliability, and cost efficiency. Experience with event streaming solutions like Apache Kafka and/or near real-time messaging Solutions such as Azure Service Bus are preferred. Experience in optimizing data pipelines to account for scale, performance, reliability, and cost efficiency is preferred. Demonstrated proficiency in relational, NoSQL, hierarchical, and entity relationship data modeling. Experience in creating easy-to-consume documentation of data processes and solutions to aid in knowledge transfer and continuity. Experienced in agile development methodologies, developing high-quality code, and DevOps best practices. Strong foundations with core Java concepts. Good understanding of Aspect Oriented Programming (AOP), Test Driven Development (TDD). Solid grasp of HTTP, RESTful web services, Linux operating systems. Coaching and mentoring less senior team member as well as conducting reviews for their work.

Qualifications: Bachelor's degree or higher in Data Science, Mathematics, Statistics, Computer Science, Information Systems, Business Information Technology, or equivalent. 5 plus years of professional experience in data engineering, data architecture, and data integration. 5 plus years of professional experience in Java development and Spring Framework. PREFERRED: Holds active Azure DP-203 (Microsoft Certified: Azure Data Engineer Associate) or equivalent. Other Azure DP certifications or equivalents are also applicable.


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About InterSources

Sourced by ZipRecruiter

In 2007, Our journey began as pioneers in the realm of technology and security. Since then, InterSources Inc. has evolved into a trusted partner, leading the way in Cloud Security, Cybersecurity, PLG Consulting, Digital Transformation, and Professional Services. With a rich history of excellence and a forward-thinking approach, we continue to secure your digital future and drive innovation. Explore our legacy of success and discover the possibilities that lie ahead.

Company size

51 - 200 Employees

Headquarters location

Fremont, CA, US

Year founded

2007

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