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Senior Backend Engineer, Data
Not specifiedFull-timeBackend DevelopmentCybersecurity
Own production backend services and data pipelines that ingest and prepare large-scale data for an enterprise cybersecurity platform. Take features from design through production, improve existing systems, and contribute to technical initiatives and on-call operations.
Responsibilities
- Design, build, and operate ingestion pipelines for internet-scale data from public and third-party sources.
- Model data schemas, partitioning, and storage layouts; clean, normalize, and deduplicate data into reliable entities.
- Maintain data quality, freshness, failure handling, backfills, and recovery processes.
- Expose data through APIs, contribute to UI changes as needed, and work across team-owned code.
- Build data-lake foundations and automate data verification and cleaning with analysts.
- Address scale and performance issues, modernize existing code, and own services in production.
- Lead technical initiatives, improve team practices, participate in on-call, and reduce alert noise by fixing root causes.
Requirements
- At least 5 years of hands-on backend development on production systems at scale, including at least 3 years building production data pipelines or data-intensive systems.
- Strong Python skills and experience designing data models and partitioning schemes.
- Experience with large-scale data ingestion from external APIs, including rate limits, pagination, retries, and idempotency.
- Experience with a modern data platform, such as Databricks.
- Understanding of network and web protocols; experience with cloud providers, containers, Kubernetes, and CI/CD.
- Evidence of end-to-end ownership from design through production, and willingness to work across APIs and frontend when needed.
- Daily hands-on use of AI coding tools and agents.
- B.Sc. in Computer Science or Computer Engineering, or equivalent experience.
Nice to have
- Hands-on experience with Databricks and PySpark.
- Experience with data lineage, data-quality tooling, and scaling SQL or NoSQL databases.