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Elastic SIEM Engineer:
The Opportunity:
Design, implement, integrate, and maintain systems and tools to automate complex cyber activities. Apply advanced consulting skills or extensive technical expertise, including full industry knowledge. Develop innovative solutions to complex problems. Work without considerable direction, and mentor and supervise team members.
You Have:
- 3+ years of experience administering Elastic Stack, including Elasticsearch, Kibana, Logstash, Beats, or Fleet
- Experience managing Elasticsearch index lifecycle policies, index templates, and data streams at scale, and building Kibana dashboards, visualizations, and lens-based analytics for security operations
- Experience with Elastic Security detection rules, alerts, and case management workflows
- Experience with log ingestion pipeline design, including parsing, enrichment, and normalization across heterogeneous log sources such as network, endpoint, identity, and cloud
- Experience with Elastic Common Schema (ECS) and mapping non-standard log sources into ECS-compliant fields
- Experience working in a DoD, IC, or federal cybersecurity environment such as SOC, SIEM operations, or defensive cyber
- Knowledge of AI/ML concepts as applied to security analytics such as anomaly detection, behavioral baselining, or threat scoring
- Ability to work on-site per program requirements, and travel up to 25% of the time
- Secret clearance
- Bachelor’s degree
Nice If You Have:
- Experience with Elastic's ML jobs, including for User and Entity Behavior Analytics (UEBA), rare process detection, or anomalous login patterns
- Experience with Elastic AI Assistant or integration of LLMs into Elastic Security workflows such as natural language querying and alert triage assistance
- Experience building or fine-tuning ML models outside Elastic, including Python, scikit-learn, and Py Torch, for security use cases such as threat detection or lateral movement scoring
- Experience with Elastic Agent fleet management at scale, including custom integrations and policy management
- Experience with cross-domain data flows and working in multi-classification environments such as IL4, IL5, or IL6
- Experience with ES|QL or EQL for advanced threat hunting and detection-as-code workflows
- Experience building SOAR-related automation around Elastic, including webhook actions, connector integrations, or n8n/XSOAR orchestration
- Experience with Elastic's transforms and runtime fields for creating enriched security datasets and risk scoring indices
- Experience with RAG architectures or vector search in Elasticsearch for security knowledge retrieval, including TTP lookup and incident context enrichment
- TS/SCI clearance
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $86,800.00 to $198,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Work Model Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
- If this position is listed as remote or hybrid, you’ll periodically work from a Booz Allen or client site facility.
- If this position is listed as onsite, you’ll work with colleagues and clients in person, as needed for the specific role.
Commitment to Non-Discrimination:
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
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About Booz Allen Hamilton

Booz Allen Hamilton
PublicSpecializing in digital transformation and artificial intelligence.
10,001+
Employees
McLean
Headquarters
Reviews
3.5
5 reviews
Work Life Balance
2.5
Compensation
3.0
Culture
2.8
Career
2.5
Management
2.0
35%
Recommend to a Friend
Pros
Great reputation in federal sector
Hybrid work options available
Established teams and processes
Cons
Poor hiring and recruitment process
Job security concerns with contract-based work
Work-life balance issues
Salary Ranges
34 data points
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Junior/L3 · Data Engineer
1 reports
$149,500
total / year
Base
$115,000
Stock
-
Bonus
-
$149,500
$149,500
Interview Experience
7 interviews
Difficulty
2.7
/ 5
Duration
21-35 weeks
Offer Rate
43%
Experience
Positive 29%
Neutral 28%
Negative 43%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Hiring Manager Interview
5
Team Interview
6
Offer
Common Questions
Technical Knowledge
Behavioral/STAR
Past Experience
System Design
Culture Fit
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