Responsibilities
- Design, develop, and maintain high-throughput batch and streaming data pipelines processing billions of records.
- Manage core datasets that support product functionality, business analytics, and machine learning applications.
- Build scalable systems for data enrichment, deduplication, identity resolution, and confidence scoring.
- Define long-term technical architecture for foundational data platforms.
- Lead multi-quarter engineering initiatives including platform migrations, major refactors, and new data infrastructure.
- Optimize trade-offs between data accuracy, timeliness, cost, and system performance in production environments.
- Take ownership of SLAs and SLOs related to data freshness, correctness, and completeness.
- Create frameworks for data quality monitoring, data reconciliation, and pipeline observability.
- Lead investigation and resolution of production data issues with a focus on root cause and prevention.
- Work closely with Product, Analytics, Data Science, Platform, and GTM teams to turn business requirements into robust data solutions.
- Serve as technical liaison for third-party data integrations and external vendor collaborations.
- Mentor senior engineering staff and help define organization-wide technical standards.
- Demonstrate leadership through active participation in design reviews, incident response, and operational accountability.
- Promote engineering best practices focused on system scalability, reliability, and long-term maintainability.
- Utilize generative AI and AI-powered coding tools to enhance developer efficiency and automate routine development tasks.
Work Arrangement
Remote (City/Region)
Team
Cross-functional collaboration with Product, Analytics, Data Science, Platform, and GTM teams.
Team
Cross-functional collaboration with Product, Analytics, Data Science, Platform, and GTM teams.
