You will serve as a technical leader responsible for architecting systems within your team's domain and driving complex, cross-team projects that support the cybersecurity platform's strategic objectives. You will fully understand and own multiple entire areas of the codebase or multiple services, working with your Manager or a Technical Director to validate your technical decisions. You will actively mentor other engineers, lead the evaluation and implementation of new technologies, and ensure all work meets high-quality pull request standards. You will collaborate across teams inside the Data Engineering org, represent your team to external stakeholders, and help move the broader organization forward through technical output, code reviews, and documentation.
Responsibilities
- Lead projects that cross teams, actively working with your Manager to set the technical vision for your team
- Take a problem and drive the projects your crew should do to solve it
- Architect systems that are within your team's domain, with guidance from Manager or Technical Director when needed
- Fully understand and own multiple entire areas of the codebase or multiple services
- Lead evaluation and implementation of new technologies that benefit your team's domain
- Ensure all work meets high-quality pull request standards and follows established engineering processes
- Collaborate across teams inside the Data Engineering org and reach out to external stakeholders for clarifications
- Mentor IC7s and IC8s on processes, technical knowledge, and quality of execution
- Work with engineers in the rest of Gen to help move the org forward
- Deliver a minimum of 4+ PRs per week (GitFlow) or 6+ PRs per week (Trunk-based development)
- Perform 2+ comprehensive code reviews per day
- Author at least 1+ RFC or Tech Spec per year
- Spend no more than 15% of work hours in meetings
- Routinely deploy to production with appropriate oversight and process adherence
- Contribute to the architecture of systems within your team's domain
Requirements
- Bachelor's degree in computer science, Data Engineering, or related technical field (master's degree preferred)
- Minimum 6-10 years of hands-on data engineering experience in large-scale, high-volume environments
- Expert proficiency in at least one of SQL and Python, with strong understanding of the other
- Extensive experience with Snowflake architecture, optimization, and performance tuning
- Demonstrated experience building Kimball dimensional data warehouses and star schema architectures
- Strong AWS cloud infrastructure experience with focus on data operations
- Production experience with either DBT or SQL Mesh for data transformation workflows
- Experience with CI/CD pipelines, GitFlow/trunk-based development, and data governance frameworks
- Knowledge of compliance requirements (GDPR, PCI-DSS) in data systems
- Proven ability to architect systems within your team's domain on your own
- Experience with Apache Kafka, event-driven architectures, and real-time analytics pipelines
- Familiarity with Apache Iceberg, data Lakehouse architectures, and modern table formats
- Experience with data warehouse performance tuning and cost optimization practices
- Experience with cohort analysis, LTV calculations, churn prediction, or marketing attribution frameworks
- Experience in cybersecurity, ad-tech, fintech, or similar high-volume industries
- Experience building feature usage analytics, behavioral analysis, or executive reporting systems