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

GuidePoint Security provides trusted cybersecurity expertise, solutions and services that help organizations make better decisions and minimize risk. By taking a three-tiered, holistic approach for evaluating security posture and ecosystems, GuidePoint enables some of the nation’s top organizations, such as Fortune 500 companies and U.S. government agencies, to identify threats, optimize resources and integrate best-fit solutions that mitigate risk.

General Description

We are looking for a skilled Security Data and Analytics Engineer to support the implementation, optimization, and operational support of data pipelines and analytics platforms. This role will engage in the development of data-source integrations, transformation workflows, and data-quality controls while providing “Wow Them” service to clients, internal customers, and co-workers.

The Security Data and Analytics Engineer must demonstrate strong data engineering, technical troubleshooting, and client communication skills. The engineer must lead through influence and apply sound business and financial awareness when making decisions involving data volume, processing cost, platform capacity, project scope, and client value.
About the North Central region SecOps Practice

The Security Operations Practice is responsible for helping clients make security, operational, and observability data reliable, usable, and available to downstream platforms and teams. We design and implement data pipelines that collect, route, transform, enrich, govern, and deliver data across complex client environments.

Our team of data engineers, SecOps engineers, consultants, architects, and platform specialists focuses on data integration, normalization, quality, routing, retention, and platform optimization. We partner with clients, account executives, project managers, source-system owners, security teams, and technology providers to create supportable data services.
Key areas of focus include:

- Establishing reliable and reusable data pipelines.

- Improving data quality, accessibility, and processing efficiency.

- Supporting security, observability, analytics, and operational use cases.

Roles and 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 and maintain pipelines that collect, route, filter, enrich, transform, mask, aggregate, and deliver data to supported 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.

Required Experience and Education:

- 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 l