Data Engineer

Summary/Objective

We are seeking a highly motivated and technically capable Data Engineer to help drive the future of our cybersecurity analytics platform, Sight. This role sits at the intersection of cybersecurity, big data analytics, visualization, and platform innovation.

Essential Functions

• Design, develop, and optimize scalable analytics solutions for large and complex datasets using Azure Data Explorer, Kusto Query Language (KQL), and related analytics technologies

• Collaborate with engineers, SMEs, and business stakeholders to model, normalize, and analyze data for reporting, operational analytics, and product-driven insights

• Build and maintain performant KQL queries, analytical workflows, data models, and reporting structures that support scalable analytics and visualization initiatives

• Design and develop interactive dashboards, reports, and visualizations within Microsoft Power BI that effectively communicate trends, operational health, risk, and business value to both technical and non-technical audiences

• Translate raw data and operational telemetry into actionable insights, meaningful metrics, and compelling data stories that support strategic and operational decision-making

• Ensure data quality, integrity, and consistency through validation, reconciliation, and analytical best practices across reporting and visualization workflows

• Research, prototype, and introduce innovative analytics methodologies, visualization concepts, and data-driven product capabilities

• Create and maintain documentation for data definitions, business logic, metrics, reporting methodologies, and analytics workflows

• Partner cross-functionally with engineering, product, and leadership teams to support long-term analytics strategy and platform innovation

Supervisory Responsibility

Not Applicable.

Work Environment

This job operates in a professional office environment or remotely as needed/required. This role routinely uses standard office equipment. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk and hear; use hands to finger, handle, or feel; and reach with hands and arms. The employee frequently is required to stand and walk. This is a largely sedentary role.

Required Education, Experience, and Skills

• Punctuality and timely attendance to external client and internal stakeholder needs
• Bachelor’s degree in Data Science, Computer Science, Cybersecurity, Statistics, Information Systems, or a related technical field OR equivalent experience
• 4+ years of experience working with analytics platforms, business intelligence solutions, data science initiatives, or enterprise data environments
• Strong experience analyzing, modeling, and visualizing large and complex datasets
• Experience building dashboards, reports, and data models within Microsoft Power BI
• Proficiency in Python, SQL, and data analytics workflows for reporting, automation, and insight generation
• Strong analytical and problem-solving skills with the ability to identify trends, patterns, anomalies, and actionable insights from data
• Ability to communicate technical findings and recommendations clearly to both technical and non-technical stakeholders
• Strong collaboration skills with the ability to work cross-functionally across engineering, product, operations, and business teams
• Demonstrated ability to independently research, prototype, and implement innovative analytics solutions

Preferred Education, Experience, and Skills

• Residence in Eastern time zone preferred
• Experience working with cybersecurity analytics platforms, vulnerability management data, security telemetry, or operational security datasets
• Experience building analytics solutions within Azure Data Explorer environments, including schema design, materialized views, analytical modeling, and query optimization
• Strong understanding of Kusto Query Language (KQL) best practices for scalable and efficient analytical workloads
• Ability to translate complex cybersecurity data into intuitive visualizations, meaningful metrics, and actionable data stories
• Experience with statistical analysis, predictive modeling, machine learning, or anomaly detection techniques
• Familiarity with data normalization strategies across multiple tools and heterogeneous data sources
• Understanding of modern cloud analytics ecosystems including Azure-based data pipelines, enrichment workflows, and scalable reporting architectures
• Experience partnering with engineering and product teams to shape analytics-driven product capabilities and reporting strategies
• Experience mentoring analysts, engineers, or technical teams on analytics best practices, visualization strategies, and data modeling approaches