Remote Senior Backend Engineer — Real-Time Data Platform

Openkrill; United States; Remote; USD 170,000 - 235,000; Full time

Benefits offered by this job

Inclusive Team

Growth Opportunities

Innovative Culture

Remote Work

Competitive Compensation including pay

Job summary

Horizon3 is a remote-first cybersecurity company building the NodeZero platform for autonomous pentests across large-scale environments. The PDP data platform team ingests NodeZero output to deliver durable, queryable records and real-time insights for enterprise customers.

You will own end-to-end streaming pipelines, tackle real-time asset identity, and evolve data models while ensuring scalability, reliability, and auditability in a distributed cloud-native setup.

Qualifications

• 4+ years of software engineering experience.
• Proficiency in Python, Go, or similar languages with experience in large-scale production codebases.
• Production experience with PostgreSQL including schema design, migrations, and query performance at scale.
• Experience building and operating large scale distributed services in AWS (or comparable cloud), with containers and orchestration (Docker, Kubernetes).
• Hands-on experience with production observability tooling (Datadog, OpenTelemetry, or similar).
• Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.

Responsibilities

• Own event-driven pipelines end to end — design, build, and operate streaming services that ingest, distribute, and process pentest operation results, including streaming and batch ETL, aggregation services, schema migrations, and replayable processing.
• Solve real-time asset identity problems — work on asset matching, asset counting, and cross-operation reconciliation, including reducing false splits and overcounting, improving matching explainability, and making asset identity available while an operation is running rather than only after completion.
• Evolve the data model — manage durable SQL-backed storage (PostgreSQL), drive schema evolution with zero-regression fidelity, and ensure data correctness, idempotency, and reliable reprocessing and failure handling.
• Drive enterprise scalability — own database performance, connection pooling, resource management, and platform reliability for a system that must handle hundreds of thousands of hosts per customer.
• Translate batch logic into streaming designs — convert batch business logic (finding enrichment, attack path analysis, host and identity correlation and other core requirements) into streaming designs without regressing fidelity for existing customers.
• Build and maintain shared platform infrastructure — contribute to common processing services that underpin features that enable customers to discover, prioritize, and report on weaknesses; support integration-test infrastructure including delta tracking and batch-transformation frameworks; build auto-discovery and code-generation tooling to accelerate new streaming service development.
• Own operational excellence — maintain ETL dashboards and data-platform monitors, participate in on-call rotations and incident response for production processing failures, manage stuck-operation workflows, define SLOs, and set up instrumentation and alerting for systems that are central to every pentest Horizon3 runs.
• Raise the technical bar — contribute through design reviews, technical writing, merge request reviews, clear API contracts with neighboring platform and product teams, and durable decision records.

Skills

Software engineering experience

Python/Go

PostgreSQL

AWS & containers

Observability tools

Education

Bachelor's degree in CS/CE or related field

Tools

Docker

Kubernetes

Kafka

Redshift

Argo/Airflow/Temporal

Job description

Horizon3 is a remote-first cybersecurity company building the NodeZero platform for autonomous pentests across large-scale environments. The PDP data platform team ingests NodeZero output to deliver durable, queryable records and real-time insights for enterprise customers.

You will own end-to-end streaming pipelines, tackle real-time asset identity, and evolve data models while ensuring scalability, reliability, and auditability in a distributed cloud-native setup.