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Data Integration Engineer Jobs (NOW HIRING)

SourceDay, Inc.

Data Integration Engineer

Austin, TX

$113K - $136K/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 ...

Conexus

$55 - $75/hr

Conexus is seeking intermediate level data integration engineers for contract work. Candidates will be supported to follow commonly established best practices as well as utilizing cutting edge ...

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How much do data integration engineer jobs pay per hour?

As of Jul 12, 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 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 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 engineers make $200,000 a year?

Data Integration Engineers with extensive experience, advanced skills in data pipelines, and proficiency in tools like ETL platforms and cloud services can earn $200,000 or more annually. High salaries are often associated with senior roles, specialized expertise, and working in industries such as finance, technology, or consulting.

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.

What engineers make $500,000 a year?

Senior data integration engineers with extensive experience, advanced skills in ETL tools, cloud platforms, and programming languages can reach or exceed a $500,000 annual salary, especially in high-cost-of-living areas or executive roles. Such compensation often includes bonuses, stock options, or other incentives and typically requires a strong track record of complex project management and technical expertise.

What engineers make $300,000 a year?

Senior data integration engineers with extensive experience, advanced skills in ETL tools, cloud platforms, and programming languages can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized expertise, and leadership responsibilities.

What does a data integration engineer do?

A data integration engineer designs, develops, and maintains systems that combine data from multiple sources to ensure accurate and efficient data flow within an organization. They work with tools like ETL (Extract, Transform, Load) processes, databases, and data pipelines, often requiring knowledge of programming languages and data modeling. Their role supports data analysis, reporting, and decision-making by ensuring data consistency and accessibility.
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Data Integration Engineer jobs near you
Infographic showing various Data Integration Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $107,501 per year, or $51.7 per hour.
Senior Data Integration Engineer

Senior Data Integration Engineer

Reflexive Concepts

Annapolis, MD • On-site

Full-time

Posted 16 days ago

Job description

Reflexive Concepts is seeking a skilled Senior Data Integration Engineer to join our team!
This role will support enterprise data modernization and integration efforts focused on ingesting, transforming, validating and managing operational data supporting critical business and mission workflows across acquisition, finance, HR, logistics, training, security and program management systems. The ideal candidate will possess a blend of database engineering, data integration and automation experience with the ability to support structured data ingestion workflows, JSON-based transformations, validation processes and enterprise application integrations including Pega-based systems serving as systems of record. This role requires a proactive and technically confident engineer who is comfortable operating in fast-paced and occasionally ambiguous environments. Successful candidates demonstrate strong ownership, initiative and sound technical judgment while working within established architectural, security and operational frameworks. The ideal candidate is capable of independently driving tasks forward, identifying gaps or risks, proposing solutions and collaborating across technical teams without requiring continuous direction or oversight.
Qualifications:
  • TS/SCI with Polygraph
  • Bachelor's degree in a technical discipline and five (5) years of experience as a Database Engineer or related technical role. Ten (10) years of experience may be substituted in lieu of a degree.
  • Experience working with relational databases and SQL-based technologies
  • Experience supporting data ingestion, transformation or ETL-style workflows
  • Experience working with structured data formats including JSON, CSV and Excel-based datasets
  • Experience writing scripts or automation utilities using Python, PowerShell or similar scripting languages
  • Experience troubleshooting data validation and operational data quality issues
  • Ability to communicate effectively with both technical and non-technical stakeholders
  • Must be able to work during core hours of M-F 10am-2pm. Exceptions will be considered on a case-by-case basis
Job Responsibilities:
  • Support ingestion of spreadsheet and structured data sources into enterprise databases and applications
  • Develop and maintain data transformation workflows including conversion of source data into JSON representations
  • Validate, troubleshoot and optimize data ingestion and synchronization processes
  • Support enterprise database operations and ensure integrity, availability and consistency of operational data
  • Assist with integration of enterprise data into Pega workflows and applications
  • Collaborate with software engineers, systems engineers and stakeholders to define data mappings, validation rules and integration requirements
  • Support development and maintenance of reporting and downstream data consumption capabilities
  • Monitor database performance and assist with troubleshooting operational issues
  • Participate in automation and modernization initiatives across enterprise services
  • Document database structures, data flows, ingestion processes and operational procedures
Desired Skills:
  • Demonstrated ability to operate independently and take ownership of technical deliverables and operational outcomes
  • Comfortable working in dynamic environments with evolving priorities, incomplete requirements and cross-team dependencies
  • Proven ability to identify technical gaps, propose solutions and proactively drive work forward with minimal oversight
  • Strong troubleshooting and analytical skills with the ability to navigate complex enterprise data environments
  • Ability to balance independent execution with appropriate stakeholder coordination and escalation
  • Strong organizational and communication skills with the ability to work effectively across engineering, operations and customer teams

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