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 generation, 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. Join us. The world can’t wait. 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 language, 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 language 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 generation, 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, 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 hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. 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. 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 disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Requirements

Must-haves

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 generation, 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.
Join us. The world can’t wait.
4+ years of experience engineering tele met ry, log, or event data pipelines at enterprise scale
Experience with a query language, 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 language 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
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 generation, 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
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.

Nice-to-haves

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Platform: booz-allen
Effort: medium

Benefits

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Professional Development