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Data Engineering Specialist Jobs (NOW HIRING)

Leidos

IL · On-site

The Leidos Digital Modernization Group seeks a Data Engineering Specialist to support the Global Management System (GMS) Team for the Global Solutions Management - Operations II (GSM-O II) contract.

AAMC

Data Engineering Specialist

Washington, DC · On-site +1

$95K - $112K/yr

Data Engineer is a key role on a centralized data engineering team that supports a wide range of data applications across the organization.This role focuses on building and maintaining reliable ...

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Lead Data Engineer

Atlanta, GA · On-site

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Lead Data Engineering Specialist **Location: Atlanta, GA (Hybrid) **Responsibilities:** - Shape industry narratives across both business and technical domains, addressing intricate challenges ...

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Engineering Specialist

Princeton, NJ · On-site

$155K - $167K/yr

Engineering Specialist in the Architecture and Engieering Exerptise Center will... * Stay current ... Lead and guide teams of developers and data engineers, enabling effective delivery of data ...

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How much do data engineering specialist jobs pay per year?

As of Jun 30, 2026, the average yearly pay for data engineering specialist in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

What are Data Engineering Specialists?

Data Engineering Specialists are professionals who design, build, and maintain the infrastructure that allows organizations to collect, store, and analyze large amounts of data. They develop data pipelines, manage databases, and ensure data is accessible, reliable, and secure for analytics and business intelligence purposes. Their work is crucial in transforming raw data into usable formats for data scientists, analysts, and business leaders.

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

To thrive as a Data Engineering Specialist, you need expertise in database management, data modeling, ETL processes, and programming languages such as SQL, Python, or Scala, often supported by a degree in computer science or a related field. Proficiency with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and data pipeline orchestration tools is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with cross-functional teams and address complex data challenges. These skills are essential for building robust, scalable data infrastructure that empowers organizations to make data-driven decisions.

How do Data Engineering Specialists typically collaborate with data scientists and analysts within an organization?

Data Engineering Specialists work closely with data scientists and analysts by designing, building, and maintaining data pipelines that ensure reliable, high-quality data is readily available. They often meet regularly with these teams to understand data requirements, troubleshoot data issues, and optimize workflows for analytics and machine learning projects. Effective collaboration involves clear communication about data structures, definitions, and timelines, as well as actively participating in code reviews and joint problem-solving sessions. This teamwork is essential for delivering impactful, data-driven solutions across the organization.

What is the difference between Data Engineering Specialist vs Data Engineer?

AspectData Engineering SpecialistData Engineer
CredentialsBachelor's in CS, certifications like AWS, GCP, or AzureBachelor's in CS, related certifications
Work EnvironmentData teams, cloud platforms, data warehousesData pipelines, databases, cloud environments
Industry UsageUsed across tech, finance, healthcareCommon in similar industries, focus on data infrastructure
Search IntentUnderstanding roles, skills, and career pathJob requirements, skills, and responsibilities

Data Engineering Specialists focus on designing and maintaining data pipelines, often with specialized skills in cloud platforms. Data Engineers build and optimize data infrastructure, working on data collection, storage, and processing. Both roles overlap in skills and environment but differ in scope and focus.

More about Data Engineering Specialist jobs
What job categories do people searching Data Engineering Specialist jobs look for? The top searched job categories for Data Engineering Specialist jobs are:
Data Engineering Specialist jobs near you
Data Engineering Specialist

Data Engineering Specialist

Leidos

IL • On-site

Full-time

Posted 10 days ago

Leidos rating

8.4

Company rating: 8.4 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

56th of 437 rated business services

Job description

The Leidos Digital Modernization Group seeks a Data Engineering Specialist to support the Global Management System (GMS) Team for the Global Solutions Management - Operations II (GSM-O II) contract. This contract includes the Operations, Sustainment, Maintenance, Repair and Defense of the Defense Information System Network (DISN) within the DOD Information Network (DODIN) in support of the Defense Information Systems Agency (DISA). It also includes support for other key tasks for DISA, including the transformation of DISA's operational mission through innovation, and support to DISA's mission partners.
The candidate must be within commuting distance of Scott AFB or Ft. Meade. At a minimum, a Secret clearance and Security + certification (or other applicable DoD 8570 IAT II certification) upon the start of employment.
The candidate will support data engineering activities, contributing to the integration and enrichment of DISN network topology data to enable advanced data correlation and analytics. They will assist in designing and implementing data enrichment pipelines, integrating multiple data sources into Confluent (Kafka) and Elastic platforms, and help maintain Kafka and Elastic clusters to support mission-critical operations. The candidate will contribute to platform sustainment and reliability by addressing operational challenges and supporting the automation of the software development lifecycle, including CI/CD pipeline development, containerization, and automated testing, while following DevOps best practices. The role involves active participation in Agile scrum teams, collaborating with team members, and sharing knowledge to support team growth. Additionally, the candidate will help develop and maintain technical documentation, ensuring solutions align with DoD security standards and compliance requirements.
As a GMS team member, you will work as part of a fast paced, Agile development and implementation team to architect, design and develop an integrated solution that expands the foundational Integrated Data Architecture platform (Confluent and ELK platform). You will work alongside others in a matrixed organization across the project.
Primary Responsibilities:
  • Contribute to data engineering efforts by supporting the integration and enrichment of DISN network topology data for advanced data correlation and analytics.
  • Participate in technical discussions with internal and external stakeholders to support solution design and implementation.
  • Develop, test, and deploy data pipelines and integration solutions across distributed systems and cloud environments, using Python, JavaScript, Java, and SQL.
  • Assist in requirements gathering and collaborate with stakeholders to design and implement data enrichment pipelines, integrating diverse data sources into Confluent (Kafka) and Elastic platforms.
  • Develop and maintain Kibana visualizations and dashboards to support operational insights.
  • Support Kafka system integrations between Elasticsearch/Logstash and other systems.
  • Collaborate within Agile scrum teams, contribute to team deliverables, and share knowledge with peers.
  • Communicate and coordinate effectively with geographically distributed team members to achieve project objectives.
  • Troubleshoot and help resolve installation, infrastructure, and system issues; report and help mitigate technical risks.
  • Develop and maintain technical documentation, including DoD requirements, interface documents, and security compliance artifacts.
  • Ensure solutions comply with DoD security standards and guidelines, and support platform sustainment and reliability by addressing operational challenges as needed

Basic Qualifications:
  • Bachelor's degree from an accredited college in a related discipline, or equivalent experience/combined education, with 4-8 years of professional experience; or 2-6 years of professional experience with a related master's degree.
  • 4+ years of experience in software engineering, data engineering, or business/data analysis, preferably within Agile/Scrum teams.
  • Hands-on software development experience with Python, Java, SQL, and working knowledge of JavaScript and HTML.
  • Experience with distributed version control systems such as Git and Bitbucket.
  • Proficiency with data analytics and visualization tools, such as Kibana, Power BI, Tableau, and the ELK stack (Elasticsearch, Logstash, Kibana).
  • Experience designing, developing, and optimizing ETL processes and data pipelines, including integration with event streaming platforms like Kafka.
  • Background in data modeling, unification, and analytics to support data-driven projects.
  • Experience implementing application and system integrations, including Kafka and Elastic platform integrations.
  • Understanding of networking and internet protocols, with experience supporting network-centric or data-driven environments.
  • Experience developing and deploying software on UNIX/Linux command line platforms.
  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders.
  • Experience with Agile project management and collaboration tools such as JIRA and Confluence.
  • Active Secret DoD Security clearance prior to start date.
  • Active Security+ Certification (or other applicable DoD 8570 IAT II certification) prior to start date.

Preferred Qualifications:
  • Experience with CI/CD techniques, containerized pipelines, and DevOps practices, including automating software delivery processes.
  • Familiarity with artificial intelligence and machine learning concepts, and interest in supporting the integration of AI/ML capabilities into data platforms.
  • Experience with data integration, storage, and analysis technologies such as Kafka, Elastic, Spark, or NiFi.
  • Hands-on experience with Kafka connector integrations and working knowledge of ksqlDB and Kafka Streams for real-time data processing.
  • Ability to develop software designs for streaming data applications, particularly using Kafka Streams or ksqlDB.
  • Experience developing and optimizing Kafka system integrations between Elasticsearch/Logstash and other systems.
  • Experience designing and implementing application deployment pipelines and developing software in containerized environments using Kubernetes and Docker.
  • Familiarity with Kubernetes deployment, Agile methodologies, and collaborative development tools.
  • Experience developing and deploying software in AWS cloud environments, including basic configuration of cloud infrastructure, networking, and security policies (GovCloud experience a plus).
  • Experience with full software lifecycle automation (design, development, testing, deployment), including production deployments.
  • Experience designing and building automated software testing pipelines using tools such as Ansible, Selenium, JMeter, Junit, or similar.
  • Experience developing and deploying software in DoD environments (DISA experience a plus), including building applications that meet DoD security standards and implementing security guidelines (e.g., STIGs).
  • Ability to support the development of DoD requirements, traceability matrices, project plans/schedules, and contribute to software systems engineering documents and interface documents (IDDs/ICDs).
  • Experience with Agile methodologies and Atlassian tools, including JIRA and Confluence, for project tracking and collaboration.
  • Ability to work effectively in remote, geographically dispersed teams, demonstrating strong communication and collaboration skills.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.
Original Posting:
April 21, 2026
For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $87,100.00 - $157,450.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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About Leidos

Sourced by ZipRecruiter

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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