Senior Data Engineer (FedRAMP)

SailPoint Technologies, Inc. is seeking a Senior Data Engineer to join their team building SailPoint Observability & Insights. In this role, you will design and build critical systems, set technical direction, and lead cross-team execution for core data platform capabilities.

Responsibilities:

• Lead architecture and implementation of scalable ETL/ELT pipelines and data services for Observability & Insights
• Own technical strategy for core data domains; align roadmap and design decisions across partner teams
• Act as primary technical lead for cross-team initiatives with clear delivery outcomes
• Set and enforce standards for data quality, governance, lineage, observability, and operational readiness
• Drive performance and cost improvements across Spark/Flink/SQL/CQL workloads and storage patterns
• Optimize graph-serving data models and access patterns so complex relationship visualizations remain responsive at extreme scale
• Partner closely with product and UI engineering to deliver low-latency experiences for graph exploration, filtering, and risk investigation
• Lead design reviews and provide high-signal code and architecture feedback
• Use AI-assisted development practices to accelerate delivery while upholding architecture, security, data governance, and code-review standards
• Partner with product, infrastructure, security, and analytics teams to define practical solutions
• Participate in on-call for critical systems and lead incident follow-throughs that improve system resilience

Requirements:

• 5+ years building production software, with substantial time in data engineering at SaaS scale
• 4+ years owning architecture for commercial data platforms or major data subsystems
• US Citizenship is required for this position due to FedRAMP support responsibilities
• Expert experience with Snowflake data modeling and query optimization
• Strong hands-on experience with dbt, Airflow, and distributed processing patterns (batch + streaming)
• Strong experience with Cassandra and familiarity with graph-oriented data systems
• Experience building or operating systems that handle billions of relationships with predictable latency and high reliability
• Deep understanding of cloud-native systems on AWS, Azure, or GCP
• Proven record of leading high-complexity projects across team/org boundaries
• Practical experience using AI-assisted software development tools (e.g., GitHub Copilot, Cursor, or Claude Code) in a professional engineering workflow, including data modeling, SQL/dbt, and pipeline development, testing, and documentation, with disciplined review before production use
• Proven ability to improve team-level delivery quality (planning, dependencies, execution, reliability)
• Strong communication skills: can explain tradeoffs to engineers, product leaders, and executives
• BS in Computer Science, Engineering, or equivalent practical experience
• Experience running data platforms with SLOs and modern observability (Grafana, Prometheus, Datadog)
• Experience instrumenting data jobs and services for performance, quality, and cost visibility
• Familiarity with IAM/IGA, compliance, security, or privacy-sensitive product domains
• Experience with Kubernetes, infrastructure-as-code, and continuous delivery for data systems
• Familiarity with data lake patterns and Spark/Flink operational tuning