About the role
Runware is building a high-performance AI media-creation platform powering instant generation of text, image, video, 3D, and audio. As our platform scales and integrations grow, we need robust, reliable, and high-throughput data systems.
We’re looking for a Data Engineer to architect and maintain our data backbone — with a special focus on high-volume logs, and performance pipelines.
You will work hand-in-hand with our Data Expert and the platform team to transform raw system activity into structured, queryable, high-value data.
🎯 Mission
Your main mission is to build, optimize, and maintain Runware’s data infrastructure.
You will ensure that logs, metrics, performance data, and events are efficiently ingested, processed, stored, and ready to be analyzed by engineering, ML, and product teams.
This role is central to:
Supporting observability & platform reliability
Enabling deep log & performance analytics
Powering internal dashboards and customer reporting
Providing clean, structured data to the Data Expert and all stakeholders
🧩 What You Will Do
Architecture & Ownership
Design, build, and maintain schemas and data models
Optimize table layout, partitioning, indexing, and compression for high-volume data
Ensure fast, efficient querying for logs, requests, metrics, and performance traces
Maintain ingestion pipelines for billions of records
Data Engineering & Pipelines
Build robust pipelines for:
API logs
Model inference logs
Error events
Usage & integration events
GPU & system metrics
Implement ETL/ELT workflows to transform raw data into analytics-ready structures
Ensure quality, reliability, and real-time availability of data sources
Performance & Log Analysis Infrastructure
Build tooling to support large-scale log analysis
Enable deep investigation into latency, throughput, errors, and bottlenecks
Provide the raw data foundation for E2E inference-time monitoring
Help debug production issues using logs and traces
Tooling & Observability Infrastructure
Work closely with DevOps, ML, and backend engineering
Integrate pipelines with monitoring tools (Prometheus, Grafana, Datadog, OpenTelemetry)
Automate ingestion and cleanup tasks
Build internal libraries or utilities to support monitoring and debugging workflows
Collaboration & Cross-Functional Support
Provide clean data interfaces for the Data Expert (dashboards, monitoring, analytics)
Support engineering teams by exposing the right logs and metrics
Contribute to debugging, RCA (root cause analysis), and performance optimization initiatives
Requirements
What We’re Looking For
Solid experience as a Data Engineer or similar role in a production environment
Strong understanding of data pipelines, streaming vs batch processing, and data modeling
Experience working with analytical databases (ClickHouse is a plus, but not mandatory)
Comfortable digging through logs, metrics, and platform data to understand system behavior
Familiarity with event-based systems, monitoring, and observability concepts
Pragmatic mindset: you care about usefulness, reliability, and performance over theory
Comfortable working cross-functionally with backend, infra, and data profiles
Startup / scale-up experience is a plus
Nice to Have
Experience with high-throughput or realtime systems
Exposure to cost monitoring, performance analytics, or platform observability
Background in AI, ML platforms, or data-heavy products
Benefits
We’re a remote-first collective, meeting in person twice a year to plan, brainstorm, celebrate wins, and enjoy some face-to-face time. We have core hours for cooperative working and calls, but outside of that your calendar is yours. Work the hours that let you perform at your peak while also building a healthy life.
Our release cycles are fast and intense, but they’re followed by real downtime. After big pushes we expect the team to unplug, recharge, and come back ready & stronger than ever for the next leap.
Generous paid time off – vacation, sick days, public holidays
Meaningful stock options – share in the upside you create
Remote-first setup – work from home anywhere we can employ you
Flexible hours – own your schedule outside core collaboration blocks
Family leave – paid maternity, paternity, and caregiver time
Company retreats – twice-yearly gatherings in inspiring locations
Originally posted on Himalayas