Cyber Security Engineer – Data Engineer (1363)

Sharp Decisions; Charlotte (NC); Hybrid; USD 110,000 - 165,000; Full time

Job summary

Sharp Decisions is seeking a Cyber Security Engineer - Data Engineer to design, build, and support scalable security data ingestion pipelines for enterprise security monitoring platforms. The role focuses on onboarding security log sources into SIEM and cloud data platforms, ensuring high-quality telemetry for threat detection, incident response, compliance, and analytics.

You will work on log ingestion, data transformation, parsing, and cloud security platforms with automation and collaboration

Qualifications

• 3+ years in cybersecurity, data engineering, or security operations.
• Hands-on with onboarding and validating log sources in SIEM/cloud data platforms.
• Experience parsing and transforming structured and unstructured data (JSON/XML/CSV).
• Knowledge of security telemetry sources across network, endpoint, cloud, and apps.
• Experience with cloud-native logging and analytics services.
• Strong troubleshooting for data ingestion pipelines and data quality.
• Understanding of logging regulations, retention, and integrity.
• Scripting in Python/PowerShell or similar automation tools.
• Ability to collaborate with cross-functional teams globally.

Responsibilities

• Design, build, and maintain scalable data ingestion pipelines for onboarding security log sources into SIEM and cloud data platforms.
• Parse, normalize, transform, and enrich log data using regex, JSON parsing, and schema mapping.
• Collaborate with application owners, infrastructure teams, cloud teams, vendors, and security stakeholders to onboard new log sources.
• Validate log integrity, completeness, timeliness, and quality of telemetry.
• Align onboarded data with enterprise standards, schemas, naming conventions, and data governance.
• Troubleshoot data ingestion, parsing, transformation, and pipeline issues across platforms.
• Create and maintain documentation for onboarding procedures, pipeline configurations, data mappings, and operational support processes.
• Partner with Detection Engineering and SOC teams to ensure logs support threat detection and response.
• Perform telemetry gap analysis to identify missing data sources and onboarding priorities.
• Support logging practices that comply with audit, regulatory, retention, and data integrity requirements.
• Improve ingestion frameworks, automation, and onboarding workflows for scalability and reliability.
• Develop automation and IaC solutions to streamline deployment and maintenance.
• Monitor pipeline performance and optimize ingestion reliability, throughput, and cost.
• Stay current with evolving cybersecurity data engineering practices and cloud security technologies.

Skills

Security data engineering

SIEM onboarding

Data ingestion pipelines

Regex/JSON parsing

Cloud security platforms

Automation / IaC

Stakeholder collaboration

Threat detection & incident response

Data governance & compliance

Python / PowerShell

Tools

Azure Data Explorer

Azure Log Analytics

SIEM platforms

Terraform

Python

Job description

Location: Charlotte, North Carolina (Hybrid)

Employment Type: Long Term Contract

Exp-: 4+ years

Job Summary

We are seeking a Cyber Security Engineer - Data Engineer to design, develop, and support scalable security data ingestion pipelines for enterprise security monitoring platforms. The ideal candidate will have experience onboarding security log sources into SIEM and cloud data platforms, ensuring high-quality security telemetry for threat detection, incident response, compliance, and security analytics.

This role requires strong expertise in log ingestion, data transformation, parsing, cloud security platforms, automation, and collaboration with security operations, infrastructure, and application teams.

Key Responsibilities

• Design, build, and maintain scalable data ingestion pipelines for onboarding 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 regex, JSON parsing, schema mapping, and data validation techniques.
• Collaborate with application owners, infrastructure teams, cloud teams, vendors, and security stakeholders to onboard new security log sources.
• Validate log integrity, completeness, timeliness, and quality to ensure reliable security telemetry.
• Align onboarded data with enterprise standards, schemas, naming conventions, and data governance requirements.
• Troubleshoot data ingestion, parsing, transformation, and pipeline issues across multiple platforms and environments.
• Create and maintain documentation for onboarding procedures, pipeline configurations, data mappings, and operational support processes.
• Partner with Detection Engineering and SOC teams to ensure logs support threat detection, investigation, response, and cyber risk visibility.
• Perform telemetry gap analysis to identify missing or incomplete security data sources and recommend onboarding priorities.
• Support logging practices that comply with audit, regulatory, retention, and data integrity requirements.
• Improve ingestion frameworks, automation, and onboarding workflows to enhance scalability, efficiency, and reliability.
• Develop automation and Infrastructure-as-Code (IaC) solutions where appropriate to streamline deployment and maintenance.
• Monitor pipeline performance and optimize ingestion reliability, throughput, and operational cost.
• Stay current with emerging cybersecurity data engineering practices, logging standards, telemetry formats, and cloud security technologies.

Required Qualifications

• Minimum 3+ years of experience in Cybersecurity, Data Engineering, Log Management, Security Operations, or a related technology discipline.
• Hands‑on experience onboarding, managing, and validating log sources within SIEM, cloud data platforms, or security analytics environments.
• Strong understanding of data parsing, normalization, transformation, and validation techniques.
• Experience working with structured and unstructured data formats including JSON, XML, CSV, and Regex.
• Knowledge of common security telemetry sources including network, endpoint, identity, cloud, infrastructure, and application logs.
• Experience with cloud platforms and cloud‑native logging, monitoring, and analytics services.
• Strong troubleshooting skills related to data ingestion pipelines, schema validation, and data quality issues.
• Understanding of regulatory and compliance requirements related to logging, auditability, data retention, and integrity.
• Experience with scripting languages such as Python, PowerShell, or similar automation tools.
• Experience using query languages to investigate and validate ingested security data.
• Strong planning, coordination, and stakeholder management skills.
• Ability to manage operational support while delivering project‑based initiatives.
• Strong analytical, communication, documentation, and problem‑solving skills.
• Ability to work effectively within a collaborative global team environment.

Preferred Skills

• Experience with Azure Data Explorer, Azure Log Analytics, or similar cloud security platforms.
• Knowledge of SIEM platforms and enterprise security monitoring solutions.
• Experience with automation, Infrastructure-as-Code (IaC), and DevSecOps practices.
• Experience in Threat Detection, Incident Response, Vulnerability Management, or Cloud Security.
• Familiarity with enterprise data governance and security compliance frameworks.

Ideal Candidate

The ideal candidate is a hands‑on Cyber Security Engineer with strong expertise in security data engineering, SIEM onboarding, cloud logging platforms, and automation. They are passionate about improving security visibility, ensuring high-quality telemetry, and collaborating across cybersecurity, infrastructure, and application teams to build scalable and reliable security data pipelines.