Senior Software Engineer
Position Overview
Our Engineering organization is a fast-growing team of collaborative, technically strong, and passionate problem solvers. We value creativity, ownership, and the drive to build meaningful technology that solves real-world security challenges. Every engineer has the opportunity to make a measurable impact-on the product, the company, and our culture. We believe in using the right tools for each problem, mentoring and learning through peer reviews, and continuously improving how we build.
The Application Data Platform team designs, builds, and maintains data-intensive applications that power customer-facing features across REST APIs and UI components. Python is our primary language, and we take pride in delivering end-to-end solutions-from frontend and API design to backend systems and databases.
The Role
We are looking for a Senior Software Engineer to join our Data Platform engineering team, focused on building systems that ingest, process, and analyze network cloud telemetry such as flow and DNS logs.
This is a high-impact, hands-on technical leadership role. You will design and scale distributed systems that power real-time detection, while influencing architecture, standards, and engineering practices across teams.
Key Responsibilities
Platform Architecture
- Design and own the foundational data infrastructure - warehouses, lakehouses, and streaming systems - that enables data and analytics teams to operate at scale.
- Architect scalable, reliable, and secure data platform solutions across cloud environments.
- Lead platform-level architectural decisions and document trade-offs clearly.
Data Infrastructure & Pipelines
- Provide platform for developers to build, deploy, and maintain ELT/ETL pipelines using modern orchestration tools.
- Own data warehouse and data lake infrastructure; manage schema evolution, partitioning strategies, and performance tuning centrally.
- Implement CDC (Change Data Capture) pipelines using Debezium or Kafka for real-time data movement.
- Establish data contracts and schema registries to enforce data quality at the platform boundary.
Observability & Data Quality
- Implement data observability to detect freshness, volume, and schema anomalies before they reach consumers.
- Define and enforce SLAs for pipeline reliability, latency, and data freshness.
- Build monitoring, alerting, and incident response runbooks for production data systems.
Security & Governance
- Implement access controls, data classification, and secrets management across all platform components.
- Ensure compliance with security frameworks (SOC 2, FedRAMP, or equivalent); remediate findings proactively.
- Collaborate with security and governance teams to align data platform with enterprise standards.
Collaboration & Mentorship
- Partner with analytics engineers, data scientists, and product managers to deliver high-quality data solutions.
- Conduct code reviews and contribute to engineering standards documentation.
- Guide and mentor junior engineers; raise the team's overall engineering bar.
Required Skills & Qualifications
Experience
- 5+ years working on production data platforms
- Track record of owning and operating platform-level systems end-to-end
Cloud & Infrastructure
- Hands-on Terraform (writing modules, state management, workspace isolation)
- Docker and Kubernetes in production (multi-tenant, scaling distribution of workloads, autoscaling)
- AWS (preferred), GCP, or Azure - compute, storage, networking, IAM
Data Stack
- Cloud data warehouse: Delta lake, Iceberg
- Streaming: Kafka, Flink, or Kinesis
- Strong Python; Rust is a plus
Data Quality & Observability
- Data contracts and schema registry experience (nice to have)
- Data observability tooling (Monte Carlo, Soda, Great Expectations, or dbt tests) (nice to have)
Soft Skills
- Can defend architectural trade-offs unprompted
- Strong written communication and async collaboration
- Ownership mentality - drives initiatives to completion independently
- Ability to communicate trade-offs.
