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Описание вакансии
Текст:
TL;DR
Software Engineer - Data Platform (AI): Building a next-generation data platform for batch and real-time integrations, analytics, and AI/ML initiatives with an accent on Kafka-based streaming, data warehousing, governance, and scalable architecture. Focus on designing low-latency data systems, driving architectural roadmaps, ensuring high availability and compliance, and mentoring engineers.
Location: United States; salary reference location: San Francisco, CA
Salary: $232,000–$348,000 annual base pay in San Francisco; compensation may be adjusted based on employee location.
Company
Vercel builds agentic infrastructure and developer products including Next.js, v0, and AI SDK.
What you will do
- Design and develop a next-generation data platform supporting batch and real-time integrations, advanced analytics, and multiple data types.
- Architect scalable data movement and processing solutions using Kafka, Kafka-based tooling, and other streaming technologies.
- Define standards for data ingestion, enrichment, storage, modeling, ETL, and warehousing with ClickHouse, Tinybird, and Snowflake.
- Partner with engineering, product, security, compliance, legal, data science, and machine learning teams to align platform architecture with business and product goals.
- Drive architectural decisions, build-versus-buy evaluations, roadmap planning, monitoring, alerting, incident response, and high-availability practices.
- Write production-grade code, mentor engineers, and establish engineering and data governance standards.
Requirements
- 8+ years of experience in data engineering, data architecture, or related roles, including at least 5 years at Principal Engineer level.
- Experience designing and operating large-scale data infrastructure in complex, fast-paced environments.
- Strong experience with Kafka and its ecosystem, ClickHouse, Tinybird, Snowflake, and broader big data frameworks.
- Proficiency with AWS, GCP, or Azure and related big data services.
- Strong knowledge of data governance, security, regulatory compliance, and protection of sensitive information.
- Ability to communicate with stakeholders, drive consensus, mentor teams, and advocate for engineering best practices.
Nice to have
- Master's degree in Computer Science, Engineering, or a related field.
- Industry recognition or notable contributions to data engineering, including publications or open-source work.
Culture & Benefits
- Inclusive workplace committed to equal opportunity and nondiscrimination.
- Total compensation may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program.
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