Observability Pipeline Engineer in , us

Energy Jobline ATTB; Us; On-site; EUR 78,000 - 177,000; Full time

Job summary

Booz Allen is seeking an Observability Pipeline Engineer to own and evolve telemetry pipelines across enterprise and government environments. You will work with Cribl, OpenTelemetry, and Splunk, applying AI to improve parsing, schema work, and data-onboarding as code.

The role emphasizes high-volume pipelines, cost management, and secure data handling, with a strong focus on upstream pipeline quality influencing dashboards and investigations.

Qualifications

• 4+ years of experience engineering telemetry, log, or event data pipelines at enterprise scale.
• Experience building and operating a telemetry routing tier such as Cribl Stream, OpenTelemetry Collector, Vector, Fluent Bit, or Logstash, including schema design, parsing, normalization, reduction, and retention tiering.
• Experience with a query language such as SPL, DQL, LogQL, PromQL, or KQL.
• Experience managing data volume, cardinality, and cost under volume-based or consumption-based licensing.
• Experience managing configuration as code, including GitOps practice and Terraform, across multiple environments.
• Experience writing production code in Python, working against REST APIs, and administering Linux and Windows systems.
• Ability to learn new query languages.
• Secret clearance
• Bachelor's degree in CS, Information Systems, or Engineering

Responsibilities

• Build and evolve the telemetry pipeline that carries logs, metrics, and events across environments.
• Engineer the Splunk log platform from architecture to data onboarding and search performance.
• Automate source onboarding so adding a data source is a pull request with code-managed config via GitOps.
• Apply AI tooling to parser, schema mapping, and normalization to reduce manual work.
• Instrument the pipeline to detect its own failures, including silent sources and cost anomalies.
• Design retention, masking, and cost-control strategies by destination to protect data and ensure provable logs.

Skills

Telemetry pipelines

Query languages

Data volume management

Infrastructure as code

Python development

System administration

Security clearance

Learning new query languages

Education

Bachelor's degree in CS, Information Systems, or Engineering

Tools

Cribl Stream

OpenTelemetry Collector

Vector

Fluent Bit

Logstash

Job description

Observability Pipeline Engineer

The Opportunity:

Are you looking for an opportunity to combine deep technical skill with big picture thinking to make an impact on the systems people depend on every day? You understand that observability starts with the data, and that every dashboard, alert, and investigation is only as good as the tele met ry underneath it. As an observability pipeline engineer on our team, you'll own the tele met ry that feeds logging, monitoring, and security analytics across commer cia l and accredited government environments.

Your customers will t rus t you not only to build and operate the pipeline in Cribl and Splunk, but to evolve it - delivering source onboarding as code, applying AI to the parser and schema work that has traditionally consumed days, and building a pipeline that detects its own failures before anyone downstream is affected.

On our team, you'll broaden your skills in OpenTele met ry and tele met ry standards. This role builds the pipeline itself. The work sits upstream of the dashboards, alerts, and searches everyone else uses, and its quality determines theirs. The ideal candidate comes from a data engineering, log platform, SIEM, or observability infrastructure background and has run high-volume pipelines in production under real cost and retention constraints.

What You'll Work On:

• Build and evolve the tele met ry pipeline that carries logs, met rics, and events across every accredited environment, including sources, parsing, enrichment, normalization, routing, and destinations.
• Engineer the Splunk log platform from distributed architecture and index design through data onboarding and search performance.
• Automate source onboarding end to end so that adding a data source is a pull request rather than a ticket, with all pipeline configuration managed as code under GitOps.
• Apply AI tooling to parser , schema mapping, and normalization, collapsing work that used to take days.
• Instrument the pipeline to detect its own failures, including silent sources, schema drift, and volume and cost anomalies, before anyone downstream notices.
• Design reduction, cardinality, retention, and masking strategies that control cost, protect sensitive data by destination, and keep the operational record provable.

You Have:

• 4+ years of experience engineering tele met ry, log, or event data pipelines at enterprise scale
• Experience building and operating a tele met ry routing tier such as Cribl Stream, OpenTele met ry Collector, Vector, Fluent Bit, or Logstash, including schema design, parsing, normalization, reduction, and retention tiering
• Experience with a query , including SPL, DQL, LogQL, PromQL, or KQL
• Experience managing data volume, cardinality, and cost under volume-based or consumption-based licensing
• Experience managing configuration as code, including infrastructure as code such as GitOps practice and Terraform, across multiple environments
• Experience writing production code in a such as Python, working against REST APIs, and administering Linux and Windows systems
• Ability to learn new query languages
• Secret clearance
• Bachelor's degree in CS, Information Systems, or Engineering

Nice If You Have:

• Experience designing OpenTele met ry Collector processors and pipelines at scale
• Experience handling PII or sensitive data in tele met ry, including masking and in-flight data-protection controls
• Experience applying AI tooling to data engineering work, including parser , schema inference, or anomaly detection on data flows and validating the output before t rus ting it
• Experience with DoD cloud environments such as Azure or AWS IL5 / IL6, including change control and continuous monitoring obligations
• Experience with CIM-compliant data engineering
• Cribl Certified Observability Engineer ( CCOE ) or equivalent certification
• Splunk Enterprise Certified Architect Certification

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, , 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 your 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.

Statement

As part of the hiring process, we will ask you to complete an verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on

your

own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited

unless permission is explicitly provided .

Work Model

Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

Remote : If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

Hybrid : If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

Onsite : If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to , status as a protected veteran or any other status protected by applicable federal, state, local, or international law.