Cyber Security Engineer – Data Engineer

SMBC•Charlotte, NC

2d•Remote

About The Position

Genesis10 is seeking a remote Cyber Security Engineer – Data Engineer for a six-month contract opportunity with a global financial institution located in Charlotte, North Carolina. This hands-on engineering role focuses on strengthening monitoring, detection, and response capabilities by building, onboarding, and maintaining security data pipelines across cloud and on-premises environments. The engineer will partner with application, infrastructure, security, and governance teams to ensure critical telemetry is collected, normalized, validated, and available for threat detection and incident response. The work involves large volumes of security telemetry and complex data-quality issues in a highly regulated financial services environment. The position pays up to $65.76 per hour. Candidates must be available and ready to work directly as Genesis10 employees. For contract roles, Genesis10 lists access to clients and a recruiting team, a career-home opportunity, a behavioral health platform, medical, dental and vision coverage, a health savings account, voluntary hospital indemnity coverage, voluntary term life insurance, 401(k), sick pay where applicable, and commuter benefits in specified locations.

Requirements

At least 3 years of relevant experience in cybersecurity, data engineering, log management, or security operations.
Hands-on experience onboarding, managing, and validating log sources in SIEM, cloud data platforms, or security analytics environments.
Strong understanding of data parsing, normalization, and transformation techniques, including regex, JSON, XML, and CSV.
Familiarity with common security telemetry sources, including network, endpoint, identity, application, cloud, and infrastructure logs.
Experience with cloud platforms and associated logging, monitoring, and analytics services.
Strong troubleshooting and problem-solving skills related to data pipelines, ingestion flows, and data-quality defects.
Understanding of compliance and regulatory expectations related to logging, retention, and data integrity.

Nice To Haves

Experience with scripting or automation tools such as Python or PowerShell.
Familiarity with query languages used to validate, investigate, and analyze ingested data.
Ability to plan, coordinate, and execute onboarding efforts across multiple teams and stakeholders.
Experience in broader cybersecurity disciplines, including threat detection, incident response, or cloud security.
Ability to work effectively and collaboratively in a global team environment.
Strong communication skills, sound judgment, and a high degree of accountability.

Responsibilities

Design, build, and maintain scalable data-ingestion pipelines to onboard security log sources into SIEM and cloud data platforms, including Azure Data Explorer and Log Analytics.
Parse, normalize, transform, and enrich structured and unstructured log data using methods such as regex, JSON parsing, schema mapping, and data validation.
Coordinate with application owners, infrastructure and cloud teams, vendors, and security stakeholders to onboard log sources and confirm end-to-end data flow.
Validate log integrity, completeness, timeliness, and quality so security telemetry is reliable and fit for use cases.
Align onboarded data with organizational standards, schemas, naming conventions, and data-governance expectations.
Troubleshoot ingestion, parsing, transformation, and pipeline issues across log sources, platforms, and environments.
Develop and maintain documentation for log-onboarding procedures, data mappings, and pipeline configurations.
Collaborate with detection engineering and SOC teams to ensure onboarded logs support threat detection and investigation requirements.
Conduct telemetry gap analysis to identify missing or incomplete data sources and recommend onboarding priorities.
Support logging and data collection practices aligned with regulatory, audit, and compliance requirements.
Improve ingestion frameworks, automation, and onboarding workflows to increase efficiency and scalability.
Monitor pipeline performance and work with stakeholders to optimize ingestion reliability, throughput, and cost efficiency.
Stay current on emerging logging standards, telemetry formats, and cybersecurity data-engineering practices.