Назад
11 дней назад

Software Engineer - Data Platform (AI)

232 000 - 348 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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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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