Data Engineer Software Developer

We are seeking a Back-End Developer to join the Real-Time Visibility (RTV) team within the Global Solution Management – Operations II (GSM-O II) contract under the Global Automations & Intelligent Network Solutions (GAINS) Team. This role focuses on designing, building, and maintaining the infrastructure and systems that collect, store, process, and analyze large volumes of network operations data for the DISN network. The position is critical for ensuring data from disparate sources—such as logs, performance metrics, events, ticketing, ordering, and CMDB systems—is readily available, reliable, and performant for business and mission use. The existing platform is built on the Elastic stack and Confluent Kafka platforms.

About the role

The ideal candidate will have a strong background in data engineering, platform operations, and integration, with experience in large-scale, mission-critical environments. As a key member of the Real-Time Visibility team, you will design and implement solutions to integrate various data sources into Confluent (Kafka) and Elastic platforms, create robust data integration solutions, and adhere to the program’s CI/CD processes and data governance practices. You will collaborate with a fast-paced, Agile development team to architect, design, and develop data integration solutions (Extract, Transform, Load) supporting a unified User Experience/User Interface (UX/UI) for a holistic single-pane-of-glass interface on the Elastic platform. Additionally, you will work with operational end users and support teams to perform requirements analysis, design, develop, and demonstrate mockups and wireframes.

Candidate must be within driving distance of Scott AFB. A Secret clearance is required upon the start of employment, and the employee must obtain their Security+ certification within 14 days of the start date.

Responsibilities

• Design, build, and maintain scalable, reliable data systems and pipelines to ingest, process, and transform large, complex, and disparate data sources for analytics and reporting.
• Unify and integrate data from multiple network operations systems into a consistent, accessible platform, ensuring data quality, accuracy, security, and compliance with DoD and DISA requirements.
• Implement solutions using Confluent Kafka, Elastic Stack, AWS, and Red Hat OpenShift (Kubernetes), including creating Kafka, Elastic, and Logstash pipelines and supporting Kibana visualizations and dashboards with React, JavaScript, and HTML.
• Develop and manage data warehouses and data lakes to support analytics, reporting, and operational dashboards, optimizing infrastructure for performance, scalability, and cost-effectiveness through automation and best practices.
• Analyze and optimize ingestion throughput, query performance, indexing strategies, and storage efficiency across Elastic and Kafka platforms.
• Automate data-related tasks such as ETL/ELT processes, data validation, cleansing, monitoring, and support CI/CD pipelines for automated build, test, and deployment.
• Collaborate with data analysts, visualization engineers, and other stakeholders to deliver integrated, actionable data solutions, and document data architecture, integration patterns, and operational procedures.
• Troubleshoot and resolve issues related to data ingestion, processing, and platform performance, storage, memory, partitioning, and cluster performance.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline and 4+ years of relevant experience.
• Hands-on experience designing, building, and maintaining data pipelines (ETL/ELT) and integrating multiple, disparate data sources.
• Experience with data warehouse and/or data lake technologies (e.g., AWS Redshift, S3, Hadoop, Snowflake, or similar).
• Proficiency with data engineering tools and languages such as Python, Java, SQL, and shell scripting.
• Experience with Elastic Stack (Elasticsearch, Logstash, Kibana) and/or Kafka for data ingestion and processing.
• Familiarity with network operations data (logs, metrics, events, ticketing, CMDB) and related data models.
• Experience with Linux/UNIX system administration and automation.
• Knowledge of data security, access controls, and compliance frameworks (DoD, DISA, RMF, STIGs).
• Experience with CI/CD pipelines, containerized pipelines, version control (Git, Bitbucket), and DevOps practices.
• Strong communication and documentation skills for collaboration and knowledge sharing.
• Must be able to commute to Scott AFB, IL for up to full-time onsite support.
• Ability to obtain interim Secret DoD Security clearance before the start date.
• Ability to obtain Security+ certification or equivalent DoD 8570 IAT II certification within 14 days of the start date.

Preferred Qualifications

• Experience with DISA, DISN, or other DoD network environments, including developing and deploying software applications that meet DoD security standards (e.g., STIGs), and knowledge of network security, encryption, and access controls in classified environments.
• Experience with big data technologies and platforms such as Kafka, Spark, NiFi, Hadoop, Elasticsearch, Logstash, Databricks, and ELK Stack for text mining, summarization, search, and entity extraction.
• Experience with cloud-based data platforms (AWS, Azure, GCP, AWS GovCloud), cloud-integrated platforms, and infrastructure as code, including networking and security policies.
• Familiarity with Kubernetes deployment, platform upgrades, patching, configuration management tools (Ansible, Puppet, Chef), and monitoring, alerting, and observability tools (Prometheus, Grafana, Elastic).
• Experience with BI tools like Kibana and developing and maintaining technical documentation and runbooks.
• Strong understanding and practical experience with Agile methodologies (Scrum, SAFe), and related tools such as Atlassian JIRA and Confluence.
• Certified Confluent Developer and Certified Elastic Engineer.
• Excellent communication and collaboration skills, with experience working remotely with geographically dispersed teams and within a matrixed organization to combine software, integration, and data engineering practices.
• Apply knowledge of system architecture, networks, and centralized logging (ELK) to support data transformation initiatives.

Pay

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.

Benefits

Pay and benefits are fundamental to any career decision. Leidos offers competitive compensation, Health and Wellness programs, Income Protection, Paid Leave, and Retirement. More details are available at www.leidos.com/careers/pay-benefits.