About Lyric
Lyric is building an AI-native, composable decision platform for the world’s most complex supply chains. Our software is used by enterprises including DHL, PepsiCo, Mondelez and Exxon. We were founded by the team behind Opex Analytics and have raised $80M.
The role
We’re hiring a Principal Software Engineer – Data Backend to raise the engineering bar across Lyric’s data-intensive systems. This is an architecture-driving, deeply hands-on IC role—not a generic data-engineering job and not a people-management position.
You’ll bring a software-engineering, scaling and optimization perspective to the data domain: shape technical direction across core backend surfaces, lead an org-level initiative, mentor strong senior engineers and remain close to design, code and production systems.
What you’ll own
• Architecture and delivery for a major data-intensive product or platform initiative—potentially across batch/stream processing, ingestion, orchestration, semantic or ontology systems, performant analytics/querying or data products
• System design for scale, reliability, maintainability, observability and data quality
• Critical code, design reviews and engineering standards across teams
• Performance and cost optimization across distributed compute, storage, query and serving paths
• Technical direction and cross-team alignment without becoming an architecture-only reviewer
• Mentoring senior engineers and strengthening the mental models and practices used across the data organization
What we’re looking for
• Typically 12–17 years of experience with sustained Principal or Staff+ scope
• Strong proof of building high-scale, data-intensive products or systems from scratch and operating them in production
• Deep coding ability and maniacal standards for code quality, testing, operability and design
• Architecture depth across distributed systems, data systems and performance trade-offs
• Principal-level technical leadership: you can lead an org-wide initiative, influence multiple teams and mentor senior engineers while staying hands-on
• Open-source-first or open-source-heavy systems experience is strongly preferred over managed-service-only assembly
• Evidence of raising both the technical bar and the people around you
Relevant backgrounds
Builders of query or analytics engines, distributed batch/streaming systems, data products, semantic/ontology layers, ingestion infrastructure or other performance-oriented data systems. Exact technology keywords matter less than the depth of engineering judgment and ownership.
Not the fit
Simple SaaS/CRUD backend, conventional ETL/BI/analytics engineering, managed-services-only data work, pure platform operations without product/SWE depth, narrow keyword expertise, or a manager/architect who no longer codes.
