SecOps Data & Analytics Engineer - North Central region (Remote in the U.S.)

guidepointsecurity; EE. UU.; A distancia; USD 110.000 - 170.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Group medical and dental insurance

Flexible time-off policy

Mobile phone and home internet stipend

Retirement plan eligibility after two‑

Pet benefit option

Descripción de la vacante

GuidePoint Security is seeking a remote SecOps Data & Analytics Engineer to build and maintain data pipelines that make security, observability, and operational data reliable for downstream analytics and detection platforms.

The role combines hands-on data engineering with client-facing consulting across multiple complex environments in the North Central U.S., with up to 10% travel for on-site work and collaboration with cross-functional teams.

Formación

• 2–5 years of experience in data engineering, log management, observability, analytics engineering, platform engineering, or a related field.
• Hands-on experience with at least one data pipeline, analytics, log-management, or observability platform.
• Experience onboarding data sources and troubleshooting ingestion, transformation, processing, or destination-delivery issues.
• Experience working with structured and unstructured data formats such as JSON, XML, CSV, and key-value pairs.
• Familiarity with cloud storage, streaming, and logging services.
• Experience producing source inventories, data mappings, validation reports, pipeline diagrams, or technical documentation.

Responsabilidades

• Configure and support data ingestion from applications, infrastructure, cloud services, security tools, and business systems using agents, APIs, webhooks, syslog, object storage, message queues, and native integrations.
• Develop pipelines that collect, route, filter, enrich, transform, mask, aggregate, and deliver data to supported destinations, including parsing, field extraction, schema mapping, timestamp handling, and normalization for structured and unstructured data.
• Validate data completeness, consistency, accuracy, timeliness, and destination delivery, troubleshooting malformed, duplicated, delayed, or missing data.
• Contribute to reusable pipeline patterns, parsers, transformation logic, validation routines, data dictionaries, and implementation standards.
• Participate in data architecture assessments, documenting source inventories, data flows, dependencies, ownership, quality issues, and recommendations.
• Communicate data-quality issues, technical risks, progress, and scope considerations to technical leads, project managers, and client stakeholders.

Conocimientos

Data engineering

Observability

Analytics engineering

Platform engineering

Consulting

Herramientas

JSON

XML

CSV

Cloud storage

Streaming services

Logging services

Descripción del empleo

Role overview

A remote SecOps Data & Analytics Engineer position focused on building and maintaining data pipelines that make security, observability, and operational data reliable for downstream analytics and detection platforms. The role combines hands‑on data engineering work with client-facing consulting across multiple complex environments in the North Central U.S. region. Up to 10% travel may be required for on‑site work.

Responsibilities

• Configure and support data ingestion from applications, infrastructure, cloud services, security tools, and business systems using agents, APIs, webhooks, syslog, object storage, message queues, and native integrations.
• Develop pipelines that collect, route, filter, enrich, transform, mask, aggregate, and deliver data to supported destinations, including parsing, field extraction, schema mapping, timestamp handling, and normalization for structured and unstructured data.
• Validate data completeness, consistency, accuracy, timeliness, and destination delivery, troubleshooting malformed, duplicated, delayed, or missing data.
• Contribute to reusable pipeline patterns, parsers, transformation logic, validation routines, data dictionaries, and implementation standards.
• Participate in data architecture assessments, documenting source inventories, data flows, dependencies, ownership, quality issues, and recommendations.
• Communicate data-quality issues, technical risks, progress, and scope considerations to technical leads, project managers, and client stakeholders.

Requirements

• Two to five years of experience in data engineering, log management, observability, analytics engineering, platform engineering, or a related field.
• Hands-on experience with at least one data pipeline, analytics, log-management, or observability platform.
• Experience onboarding data sources and troubleshooting ingestion, transformation, processing, or destination-delivery issues.
• Experience working with structured and unstructured data formats such as JSON, XML, CSV, and key-value pairs.
• Familiarity with cloud storage, streaming, and logging services.
• Experience producing source inventories, data mappings, validation reports, pipeline diagrams, or technical documentation.

Nice to have

• Client-facing consulting or professional services experience.
• Familiarity with retention strategies and AI-enabled data tooling.
• Collaboration with SecOps engineers on SIEM, detection, investigation, or automation use cases.

Benefits and work setup

• Remote work within the U.S., with up to 10% travel.
• Group medical and dental insurance plans with employer premium contributions for employees and family coverage.
• Twelve corporate holidays plus a flexible time-off program.
• Mobile phone and home internet allowance.
• Retirement plan eligibility after two months.
• Pet benefit option.