Elastic Data Engineer

JCS Solutions LLC•Adelphi, MD

15d•$148,000 - $162,000

About The Position

JCS Solutions’ C5ISR Center CSSP Cloud Operations Team is seeking an Elastic Data Engineer to design, maintain, and optimize enterprise data-ingestion and analytics capabilities within a Department of Defense cybersecurity environment. The engineer will manage Elastic Stack data pipelines, integrate cybersecurity and operational telemetry, improve data quality and platform performance, and support dashboards, alerting, threat detection, incident response, and compliance reporting.

Requirements

Strong knowledge of Elasticsearch, Logstash, Kibana, Elastic Agent, Fleet, and Beats.
Experience developing high-volume logging or cybersecurity-telemetry pipelines.
Knowledge of Elasticsearch clusters, indices, shards, mappings, templates, and data streams.
Experience with Logstash filters, ingest pipelines, JSON, XML, CSV, syslog, and Windows event data.
Experience with Index Lifecycle Management, retention, rollover, and data-tiering strategies.
Linux administration and scripting experience using Python, PowerShell, or Bash.
Experience with REST APIs, Git, networking, TLS, certificates, and access controls.
Understanding security monitoring, threat detection, incident response, and vulnerability management.
Strong troubleshooting, documentation, and communication skills.
Requires a BS with 4-8 years of prior relevant experience or Master’s with 2-6 years of prior relevant experience.
Active or obtainable DOD TS/SCI clearance.

Nice To Haves

Experience supporting SOC, CSSP, SIEM, or enterprise observability platform.
Experience with Elastic Security, AWS, AWS GovCloud, Kafka, Docker, or Kubernetes.
Familiarity with Zero Trust, RMF, DISA STIGs, and federal logging requirements.
Elastic, AWS, Security+, GIAC, or CISSP certification.

Responsibilities

Design and develop data pipelines for cybersecurity, cloud, network, endpoint, application, identity, and infrastructure telemetry.
Collect, ingest, transform, normalize, enrich, and route structured and unstructured data from multiple enterprise sources.
Create and maintain standardized data schemas, field mappings, naming conventions, and data models.
Parse complex log formats including JSON, XML, CSV, syslog, Windows Event Logs, and custom application data.
Develop data-quality controls to identify missing, duplicated, malformed, delayed, or inconsistent records.
Perform data validation, reconciliation, cleansing, deduplication, and enrichment.
Map source data to Elastic Common Schema or other approved enterprise data standards.
Build reusable parsing rules, transformation logic, lookup tables, and enrichment workflows.
Integrate data from REST APIs, databases, message queues, cloud services, files, and third-party security platforms.
Support high-volume, near-real-time data ingestion and event-processing requirements.
Analyze data flows to identify ingestion gaps, bottlenecks, field inconsistencies, and source-system issues.
Collaborate with cybersecurity analysts and detection engineers to ensure data supports threat hunting, alerting, incident response, and reporting use cases.
Document data sources, schemas, transformations, lineage, dependencies, retention requirements, and onboarding procedures.
Support data governance, metadata management, data classification, retention, and access-control requirements.
Use Python, SQL, PowerShell, Bash, or similar tools for data processing, automation, validation, and troubleshooting.
Apply Git-based version control and testing practices to data pipelines, schemas, and transformation logic.
Troubleshoot data loss, timestamp issues, encoding problems, mapping conflicts, parsing failures, and ingestion delays.
Work with cloud and infrastructure teams to onboard data sources.
Maintain strong knowledge of cybersecurity telemetry, data engineering principles, ETL/ELT processes, APIs, and large-scale event data.