Responsibilities
- Design and deploy full lifecycle data systems encompassing change data capture, real-time streaming, schema strategy, data transformation, warehouse and mart modeling, and ready-to-use outputs using infrastructure-as-code and automation-first practices.
- Develop fault-tolerant, multi-region database architectures with automated replication, failover, and disaster recovery capabilities.
- Design streaming data pipelines with strong emphasis on data correctness, reproducibility, and support for evolving schemas.
- Define, document, and maintain data mart structures to enable self-service analytics and external data product usage.
- Implement comprehensive monitoring, alerting, and data quality observability across all data platform components.
- Lead efforts in identifying, classifying, and securing personally identifiable information, including lineage tracking, access policies, and encryption, in coordination with security teams.
- Guide engineering teams through mentorship and establish consistent architectural best practices for data platform development.
- Incorporate cost efficiency of compute and storage resources as a core consideration in system design decisions.
Work Arrangement
Remote (Worldwide)
Other
- Written-first communication — designs, ADRs, and runbooks live in the repo.
- Ownership and bias to action — driving ambiguous problems to working systems without waiting for the next step.
- Influence without authority — building consensus and holding the line on governance when it matters.
- Principled prioritization — protecting the critical path and explaining why decisions were made.
- Stakeholder and executive communication — translating complex technical reality into clear risk, cost, and timeline.
- Mentorship — leveling up engineers through design reviews, pairing, and documentation.
- Self-awareness and collaboration — knowing personal edges and partnering well across application, analytics, SRE, and security.
