Lead Information Security Engineer

Jobgether; Oregon; Hybrid; USD 127,000 - 189,000; Full time

Benefits offered by this job

Remote work flexibility

Competitive salary

Healthcare benefits

Retirement benefits

Professional development

Job summary

Jobgether seeks a Lead Information Security Engineer in the United States to guide data engineering for security analytics. You will build scalable pipelines and trusted metrics, enriching findings with context to drive remediation.

You will mentor engineers, establish engineering standards, and advance automation and AI-enabled security capabilities in a collaborative, globally connected environment.

Qualifications

• Bachelor's degree or equivalent professional experience.
• At least six years in security engineering, data engineering, or a related field.
• Strong leadership in projects or small teams.

Responsibilities

• Lead security data engineering initiatives and cross‑functional projects.
• Integrate security data from multiple platforms and normalize findings.
• Develop reusable data products and governed data pipelines.
• Design Snowflake data models and reliable SQL transformations.
• Establish data governance, lineage, and quality practices.
• Define KPIs and KRIs aligned with security strategy.

Skills

Python

SQL

Data modeling

APIs

Snowflake

dbt

Airflow

Cloud platforms

Security analytics

KPI/KRI metrics

Education

Bachelor's degree or equivalent

Tools

Snowflake

dbt

Airflow

Power BI

GitHub Advanced Security

CI/CD

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Lead Information Security Engineer based in the United States. In this role, you will lead the development of advanced security data engineering and analytics capabilities that help organizations identify, prioritize, and reduce cyber risk. You will integrate and enrich data from multiple security, cloud, application, identity, and governance platforms to transform complex information into actionable intelligence. Combining hands‑on engineering expertise with technical leadership, you will build scalable data pipelines, trusted metrics, and reusable data products that strengthen security decision‑making. You will collaborate with security specialists, data engineering teams, risk leaders, and business stakeholders to improve visibility into vulnerabilities, control effectiveness, and remediation outcomes. You will also help establish engineering standards, mentor technical colleagues, and support the evolution of automation and AI‑enabled security capabilities. This opportunity offers a meaningful scope of impact within a collaborative, globally connected environment focused on innovation, measurable risk reduction, and continuous improvement.

Accountabilities

• Lead security data engineering initiatives: Provide technical direction for complex security data projects and cross‑functional initiatives, overseeing solution design, implementation, delivery, and ongoing operational ownership.
• Integrate security data sources: Build scalable data pipelines, applications, APIs, and automation to ingest information from security, cloud, application, endpoint, identity, vulnerability, governance, and risk management platforms.
• Transform data into actionable intelligence: Deduplicate, correlate, normalize, and enrich security findings with asset ownership, business context, control information, and risk indicators to improve prioritization and remediation.
• Develop governed data products: Design and deliver reusable security data products through enterprise data platforms, leveraging Snowflake and established data engineering practices to make security information reliable, accessible, and reusable.
• Optimize data architecture and performance: Develop and maintain Snowflake data models, SQL transformations, queries, and compute patterns while ensuring data quality, performance, access controls, traceability, and cost efficiency.
• Establish data governance practices: Collaborate with enterprise data, governance, and security teams to implement sustainable practices for data ingestion, transformation, role‑based access, lineage, metadata, quality assurance, and lifecycle management.
• Define security performance metrics: Develop and operationalize key performance indicators (KPIs), key risk indicators (KRIs), control‑effectiveness measures, thresholds, targets, and calculation methodologies aligned with security strategy and risk objectives.
• Ensure metric consistency and accountability: Establish documented definitions, authoritative data sources, clear ownership, validation processes, refresh schedules, version control, and traceability between metrics, risks, controls, and remediation activities.
• Deliver meaningful reporting and dashboards: Build technology‑agnostic dashboards, scorecards, reporting capabilities, and reusable services that allow stakeholders to move from executive‑level indicators to the underlying assets, controls, findings, and remediation actions.
• Translate analytics into recommendations: Identify emerging trends, systemic risks, concentrated exposures, control gaps, and remediation opportunities, communicating clear recommendations to leadership and technical teams.
• Support automation and AI innovation: Build strong data foundations for security automation and future AI‑enabled capabilities, including integrations based on the Model Context Protocol (MCP).
• Mentor and develop technical talent: Guide engineers through technical design, peer reviews, training, knowledge sharing, and the adoption of consistent engineering standards.
• Evaluate technologies and improve efficiency: Assess emerging security, data, and analytics technologies, recommending solutions that maximize business value, reduce manual work, and minimize unnecessary vendor dependency.
• Communicate technical direction: Clearly explain architecture decisions, technical trade‑offs, delivery progress, risks, and recommendations to engineers, business stakeholders, control owners, and senior leaders.
• Drive measurable security outcomes: Ensure that data products and reporting improve risk prioritization, control visibility, remediation effectiveness, security debt measurement, and the ability to quantify the value of security initiatives.

Requirements

• Education: Bachelor's degree in arts, sciences, or a related discipline, or equivalent professional experience. A master's degree or relevant professional certifications is preferred.
• Professional experience: At least six years of experience in security engineering, information systems, data engineering, security analytics, application development, or a closely related field, including substantial hands‑on technical delivery.
• Technical leadership: Demonstrated experience leading technical projects or small teams, guiding solution design, mentoring colleagues, and managing initiatives from planning through delivery.
• Information security expertise: Strong understanding of information security and practical experience working with vulnerability, exposure, cloud, application, endpoint, identity, governance, and security control data.
• Data engineering proficiency: Advanced hands‑on skills in Python, SQL, APIs, data modeling, databases, and automated data pipelines, with experience developing and maintaining reliable data services.
• Cloud data platforms: Experience building analytical models, pipelines, or data products using Snowflake, an enterprise data platform, or a comparable cloud data ecosystem.
• Cloud application development: Experience designing, developing, deploying, and operating applications or data services on AWS or another major cloud platform.
• Security metrics and risk measurement: Proven ability to define and operationalize KPIs, KRIs, control‑effectiveness measures, and outcome‑based metrics, including calculation logic, thresholds, targets, ownership, and validation.
• Data governance: Working knowledge of governed data‑product practices, including role‑based access, data lineage, metadata management, data quality, ownership, and secure data sharing.
• Analytics and reporting: Experience with security analytics, business intelligence, dashboard development, data visualization, and executive or operational reporting.
• Security risk management: Familiarity with exposure management, vulnerability prioritization, risk‑based remediation, security program measurement, and control‑effectiveness reporting.
• Engineering tools and platforms: Experience with technologies such as Snowflake, dbt, Airflow, Atlan, Power BI, Git‑based development workflows, infrastructure as code, CI/CD, containers, or serverless application patterns is preferred.
• Security ecosystem knowledge: Familiarity with platforms such as Wiz, GitHub Advanced Security, GitGuardian, CrowdStrike, Tenable, Nucleus, LogicGate, or comparable security technologies is an advantage.
• Emerging technology experience: Experience with AI‑enabled integrations, automation, or MCP‑based solutions is preferred.
• Professional certifications: Relevant certifications such as CISSP, CISA, CCSP, CGRC, CompTIA CASP+, OSCP, or CEH, as well as relevant cloud, security, data engineering, analytics, or architecture certifications, are advantageous.
• Communication skills: Excellent written and verbal communication, with the ability to explain complex technical and risk concepts clearly to executives, engineers, control owners, and remediation teams.
• Analytical and strategic thinking: Strong investigative, analytical, and problem‑solving skills, with the ability to translate business and security requirements into maintainable technical solutions, measurable outcomes, and actionable recommendations.
• Stakeholder management: Demonstrated ability to influence, negotiate, manage change, and collaborate across technical, operational, risk, governance, and business functions.
• Autonomy and adaptability: Ability to balance strategic architecture with hands‑on engineering, manage competing priorities, work with limited direction, and deliver results in a dynamic environment.

Benefits

• Competitive base salary: Annual compensation ranging from $126,710 to $188,840, depending on qualifications, skills, experience, and work location.
• Annual bonus program: Eligibility for an annual bonus program applicable to all positions.
• Long‑term incentives: Certain employees may qualify for additional long‑term, equity‑based performance incentive programs.
• Comprehensive healthcare benefits: Access to a broad benefits package designed to support employee health and well‑being.
• Retirement benefits: Retirement plans and related benefits to support long‑term financial security.
• Remote work flexibility: Remote working arrangements for eligible employees based in the United States.
• Global collaboration: Opportunities to work with knowledgeable, supportive colleagues and diverse teams across international locations.
• Professional development: Opportunities to expand technical expertise, share knowledge, mentor others, and contribute to innovative security and data engineering initiatives.
• Innovation‑focused environment: The opportunity to influence security architecture, strengthen enterprise risk management, and develop data‑driven capabilities with measurable organizational impact.
• Inclusive workplace culture: A collaborative and respectful environment that values diverse perspectives, individual contributions, and continuous learning.