Elasticsearch Data Engineer at Leidos

Description

The Leidos Digital Modernization Group seeks a skilled Data Engineer to support the Enterprise Situational Awareness/Common Operational Picture (SA/COP) Team. The ideal candidate will have a strong background in data integration, model development, and system architecture, along with experience in maintaining and optimizing data pipelines. This role requires a collaborative mindset and the ability to work in a matrixed organization, combining data engineering with DevOps practices to enhance enterprise data governance and embrace a culture to support critical data transformation, analysis, and visualization initiatives.

The Leidos Digital Modernization Sector provides a diverse portfolio of systems, solutions, and services covering land, sea, air, space, and cyberspace for customers worldwide. Solutions for Defense include enterprise and mission IT, large-scale intelligence systems, command and control, geospatial and data analytics, cybersecurity, logistics, training, and intelligence analysis and operations support. Our team is solving the world’s toughest security challenges for customers with “can’t fail” missions.

Joint Management Tool (JMT) supports the effective planning, deployment, trouble management, and decommissioning of deployed and non-deployed Satellite Communications (SATCOM) resources, specifically those supporting Department of Defense (DoD), mission partner (other U.S. federal agency), and international partner missions. Through the implementation of automated workflows and dynamic user interfaces, the JMT system strives to streamline business processes and significantly reduce the recurrence and impact of human error by functioning as a homogenous platform through which SATCOM planners, provisioners, operators, and customers can seamlessly coordinate SATCOM requests. 

As a key SA/COP team member, you will work as part of a fast paced, Agile development and implementation team to architect, design and develop a data engineering detailed design solution that supports a unified data integrated platform that expands the foundational Integrated Data Architecture platform (Confluent and ELK platform). You will work along side others in a dedicated scrum team in support for operational end user and support team requirements.

Primary Responsibilities:

• Data Analysis & Problem Solving: Analyze quantitative and qualitative data to solve stakeholder problems and improve business efficiency. Design, implement, and document solutions as repeatable processes.

• ETL Pipeline Development: Perform extraction, transformation, and load (ETL) tasks. Develop and integrate data sets from diverse environments to support use cases involving network, performance, application, and configuration data.

• Data Modeling & Management: Develop, test, and maintain both physical and logical data models. Ensure consistency, quality, accuracy, and security of data by managing relevant metadata in support of the project. Identify and resolve Elasticsearch issues, including slow queries and indexing problems.

• Adherence to Governance & SecDevOps: Follow GMS Data Governance and SecDevOps policies to develop, test, deploy, and maintain data engineering pipelines.

• Cross-Team Collaboration: Work within a matrixed organization to collaborate with primary project leadership while maintaining standard practices with GMS core teams. Combine software and data engineering practices to strengthen enterprise data governance.

• System Architecture & Data Transformation: Apply knowledge of system architecture, network, and Centralized Logging (ELK) to support data transformation efforts.

• Data Analytics & Visualization: Secure, maintain, optimize, and document analytics and visualization solutions, including some design and build responsibilities.

• Agile Practices: Follow Agile scrum practices in daily operations.

• Elastic Cluster Management: Deploy and manage Elastic clusters on Kubernetes in both on-premise and cloud environments.

• Platform Expansion: Expand data platforms and analytics solutions using Elastic and Confluent platforms, focusing on SATCOM metadata for dashboard and reporting visualizations.

• Customer Visualization Support: Support customer-driven visualization requirements and collaborate on data integration and Kibana dashboard development.

Basic Qualifications:

• 8+ years of experience and a B.S. Additional experience may be accepted in lieu of degree.

• Proficiency with Data Management platforms and strong communication skills for effective collaboration with virtual teams of data engineers and DevOps engineers.

• Experience following a software development lifecycle, with the ability to develop and maintain production-quality code.

• Must hold an active Secret DoD Security clearance.

Preferred Qualifications:

• Experience automating data cleansing, formatting, staging, and transformation processes.

• Proficiency with text mining tools, summarization, search (ELK Stack), entity extraction, training set generation, and anomaly detection.

• Familiarity with CI/CD techniques for developing and releasing software through containerized pipelines.

• Knowledge of BI tools (e.g., Kibana, Splunk) and experience with developing search and analytics applications.

• Experience with Elasticsearch, Logstash, Kibana, Kafka, ksql, NiFi, Apache Spark, ServiceNow.

• Certified Elastic Engineer with experience developing logstash and ingest pipelines.

• Experience developing in Confluent ksql and kstreams for data ETL purposes

• Familiarity with Kubernetes and deployment of containers.

• Experience with Agile methodologies and related tools.

Original Posting Date:

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:

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.