SecOps Data & Analytics Engineer — Remote (North Central)

GuidePoint Security LLC; Oregon; Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Remote work

Medical Insurance

Dental Insurance

FTO (Flexible Time Off)

Phone stipend

Retirement plan

Job summary

GuidePoint Security LLC is seeking a skilled Security Data and Analytics Engineer to support data pipelines, analytics platforms, and data-source integrations for client environments. You will develop transformation workflows, enforce data quality, and optimize processing costs while communicating with clients and internal teams.

The role sits within the North Central SecOps Practice, focusing on reliable, auditable data that supports SIEM, detection, investigation, and automation use cases.

Qualifications

• Two to five years of experience in data engineering, log management, observability, analytics engineering, platform engineering, or 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, key-value data, syslog, or CEF.
• Understanding of APIs, authentication, certificates, service accounts, network connectivity, and integration concepts.
• Basic scripting experience with Python, PowerShell, JavaScript, or similar language.
• Familiarity with SQL, platform-specific query languages, or data transformation languages.
• Bachelor’s degree in data engineering, information technology, computer science, cybersecurity, or related field, or equivalent professional and military experience.
• Embraces emerging technologies, including AI tools, to work smarter, solve problems, and drive better business outcomes.

Responsibilities

• Configure and support data ingestion from applications, infrastructure, cloud services, security tools, and business systems using multiple integration methods.
• Develop and maintain pipelines that collect, route, filter, enrich, transform, mask, aggregate, and deliver data to destinations.
• Implement parsing, field extraction, schema mapping, timestamp handling, data-type conversion, and normalization for structured and unstructured data.
• Validate data completeness, consistency, accuracy, timeliness, and destination delivery while 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 and document source inventories, data flows, dependencies, ownership, quality issues, and recommendations.
• Maintain awareness of data pipeline, analytics, log-management, observability, cloud, and emerging AI-enabled data technologies.
• Execute technical work across multiple client environments while managing delivery priorities, dependencies, and source-system coordination.
• Communicate data-quality issues, technical risks, progress, and scope considerations to technical leads, project managers, and client stakeholders.
• Support regional delivery priorities and collaborate with SecOps engineers when data pipelines support SIEM, detection, investigation, or automation requirements.

Skills

Data engineering

Observability

Analytics engineering

Platform engineering

Python

SQL

Education

Bachelor’s degree in data engineering / related field

Tools

Cribl

Datadog

Dynatrace

Splunk

Elastic

AWS

Azure

Google Cloud

Job description

GuidePoint Security LLC is seeking a skilled Security Data and Analytics Engineer to support data pipelines, analytics platforms, and data-source integrations for client environments. You will develop transformation workflows, enforce data quality, and optimize processing costs while communicating with clients and internal teams.

The role sits within the North Central SecOps Practice, focusing on reliable, auditable data that supports SIEM, detection, investigation, and automation use cases.