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Data Integration Engineer Jobs in Colorado (NOW HIRING)

ZVA Integration Engineer

Denver, CO

$106K - $143K/yr

CCaaS Integration Engineer Team: Customer Experience / Integrations & Professional Services Level ... Exchange data in real time or near real time * Trigger workflows and events across systems

Software Integration Engineer

Aurora, CO · On-site

$106K - $142K/yr

Knowledge of data exchange protocols (e.g., REST, SOAP) * Ability to manage software integration projects REQUIRED SKILLS * Proficiency in programming languages (e.g., Java, Python) * Strong ...

Software Integration Engineer

Aurora, CO

$106K - $142K/yr

Knowledge of data exchange protocols (e.g., REST, SOAP) * Ability to manage software integration projects REQUIRED SKILLS * Proficiency in programming languages (e.g., Java, Python) * Strong ...

As a Systems Integration Engineer, you will integrate Government Off-the-Shelf (GOTS) software into ... Advanced proficiency in log, flow data, and PCAP analysis. * Ability to develop processes and tools ...

As a Systems Integration Engineer, you will integrate Government Off-the-Shelf (GOTS) software into ... Advanced proficiency in log, flow data, and PCAP analysis. * Ability to develop processes and tools ...

Mission Integration Engineer

Denver, CO · On-site

$150K - $180K/yr

... data flows, operational workflows, and mission-specific analytics. * Coordinate V&V execution ... integration, systems engineering, technical sales, mission operations, software platform ...

Integration Engineer II- AI & Engineering

Denver, CO · Hybrid

$107K - $144K/yr

Integration Engineer II- AI & Engineering Join our AI & Engineering team in transforming technology ... Implement and manage Electronic Data Interchange (EDI) processes, including configuration of ...

Software Integration Engineer

Denver, CO · On-site

$107K - $144K/yr

As a Software Integration Engineer at True Anomaly, you will operate across the full mission ... data analysis systems * Lead architectural improvements through hands-on implementation ...

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Data Integration Engineer information

See Colorado salary details

$10

$54

$88

How much do data integration engineer jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for data integration engineer in Colorado is $54.35, according to ZipRecruiter salary data. Most workers in this role earn between $45.77 and $61.15 per hour, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, manage, and oversee data pipelines and infrastructure. Data engineers continue to be essential for building scalable systems, ensuring data quality, and integrating AI tools effectively within data workflows.

Is data integration a good career?

Data Integration Engineers design and implement systems to combine data from multiple sources, often using tools like ETL processes and data warehouses. The role is in demand across industries such as finance, healthcare, and technology, offering opportunities for growth, certifications, and skill development in SQL, scripting, and cloud platforms. It can provide a stable career with competitive salaries and evolving responsibilities as data needs grow.

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 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?

Senior data integration engineers with extensive experience, advanced skills in ETL tools, cloud platforms, and programming languages can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Compensation often includes bonuses, stock options, and other incentives for top-tier professionals in this field.

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 often use tools like ETL (Extract, Transform, Load) processes, data pipelines, and scripting languages to automate data transfer and ensure data quality. Strong knowledge of databases, programming, and data modeling is essential for this role.
What are popular job titles related to Data Integration Engineer jobs in Colorado? For Data Integration Engineer jobs in Colorado, the most frequently searched job titles are:
Senior Elastic Stack Data Integration Engineer - DOD

Senior Elastic Stack Data Integration Engineer - DOD

Innovim

Colorado Springs, CO

$120K - $159K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago


Job description

Senior Elastic Stack Data Integration Engineer - DOD

INNOVIM is seeking a Senior Elastic Stack Data Integration Engineer supports the Missile Defense Agency (MDA) on the Integrated Research and Development for Enterprise Solutions (IRES) contract.

The Senior Elastic Stack Data Integration Engineer will serve as the primary technical authority for designing, building, and maintaining data ingestion pipelines supporting Elastic SIEM. This role focuses on creating scalable, resilient Logstash architectures; developing advanced pipeline logic; normalizing, enriching, and transforming security telemetry; and ensuring reliable delivery of high-fidelity data to Elasticsearch.

Location: Schriever Space Force Base, Colorado Springs, CO or Redstone Arsenal, Huntsville, AL Relocation Assistance: None available at this time Remote/Telework: NO - Not available for this position Clearance Type: DoD Secret Shift: Day shift Position Closes: 6/18/26 Key Responsibilities:

  • Architect, build, and maintain Logstash pipelines to ingest and transform logs from diverse systems, including network devices, servers, cloud services, and security platforms.
  • Implement parsing, grok patterns, JSON transformations, conditional routing, enrichment logic, and ECS mapping.
  • Optimize pipeline performance, resiliency, and scalability (e.g., persistent queues, pipeline workers, memory tuning, load balancing).
  • Ensure all ingested data aligns to ECS (Elastic Common Schema) or internal schema requirements.
  • Implement data enrichment workflows (GeoIP, threat intel lookups, metadata injection).
  • Validate data completeness, integrity, and fidelity across ingestion flows.
  • Maintain and optimize Logstash clusters, including version management, scaling, tuning, and high-availability configurations.
  • Manage integrations with Beats, Elastic Agent, Kafka, syslog endpoints, and custom data collectors.
  • Monitor ingestion throughput, latency, and error rates; implement proactive alerting and troubleshooting processes.
  • Create and maintain technical documentation, including pipeline diagrams, data flow maps, runbooks, and schema references.
  • Establish enterprise standards for parsing, enrichment, normalization, and ingestion patterns.
  • Support internal and external audits by documenting data handling flows and pipeline logic.
  • Work closely with SIEM integration engineers to align pipelines with customer environments and logging requirements.
  • Partner with detection engineering teams to ensure data supports analytic coverage and rule development.
  • Collaborate with infrastructure and platform operations for deployment, scaling, and reliability engineering.

The successful candidate will have:

  • Demonstrated ability to work independently, drive pipeline architecture decisions, and mentor junior engineers.
  • Strong documentation, workflow diagramming, and communication skills.
  • Deep command of Logstash architecture, patterns, and performance optimization.
  • Mastery of parsing, enrichment, normalization, and ECS alignment.
  • Strong understanding of network protocols, logging patterns, and telemetry generation from enterprise systems.
  • Advanced troubleshooting skills across data ingestion, pipeline logic, and Elastic Stack processing layers.
  • Capability to design scalable, HA ingestion workflows with clear operational boundaries.
  • Ability to conduct data modeling, schema design, and transformation mapping.
  • Effective at interfacing with multiple teams, gathering requirements, and aligning pipeline designs with SIEM analytics needs.
  • Focused on reliability, maintainability, and observability across all pipeline components.
  • Strong attention to detail and a disciplined approach to documentation, versioning, and configuration management.

Basic Requirements:

  • Must have 10, or more, years of general (full-time) work experience. May be reduced with completion of advanced education
  • Must have 5, or more, years of experience in log ingestion, data engineering, or SIEM pipeline development.
  • Must have 2, or more, years of experience in a lead or senior role, mentoring and guiding other team members.
  • Must have a strong background in Elastic Stack components (Elasticsearch, Kibana, Beats, Elastic Agent).
  • Must have experience with data ingestion, processing, and enrichment techniques.
  • Must have hands-on experience ingesting, processing, and normalizing diverse log types (Windows events, syslog, firewall logs, cloud telemetry, security tooling).
  • Must be proficient with Linux administration, system-level debugging, and CLI-based operations.
  • Must have a DoD 8570.01-M IAT Level II certification with Continuing Education (CE) - (CCNA-Security, CySA+, GICSP, GSEC, Security+ CE, CND, SSCP)
  • Must have an active DoD Secret Security Clearance
  • Must be able to obtain an active DoD Top Secret Security Clearance

Desired Requirements:

  • Be an Elastic Certified Engineer or have relevant Elastic Stack certifications.
  • Have strong experience integrating Kafka, Redis, or other message bus technologies into ingestion workflows.
  • Be proficient with scripting in Python, Bash, or PowerShell for automation and data validation.
  • Have experience designing geo-distributed or multi-cluster ingestion architectures.
  • Have knowledge of threat intelligence ingestion, correlation data enrichment, and advanced ECS mapping.
  • Have experience with CI/CD pipelines, GitOps workflows, or Infrastructure-as-Code (Terraform, Ansible).
  • Be familiar with data quality assurance frameworks and pipeline testing methodologies.
  • Have knowledge of cloud-native logging architectures (AWS Firehose, Azure Event Hub, GCP Logging).

This position is expected to pay $130,000 – $150,000 annually; depending on experience, education, and any certifications that are directly related to the position.

IDS is committed to providing superior work in the fields of science, engineering, data analytics and technology to government agencies. We offer competitive compensation packages, including comprehensive nationwide Medical/Dental/Vision insurance programs, life insurance, matching 401k contribution and Educational/Training support.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.