обновлено 14 дней назад
Data Platform Engineer (AI)
200 000 - 250 000$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Platform Engineer (AI): Building software, services, APIs, connectors, and orchestration capabilities that connect enterprise systems and make data usable across applications, analytics, and AI with an accent on reusable integrations, query performance, and reliable data movement. Focus on designing concurrent and distributed workloads, handling failures and resource constraints, and taking data platform capabilities from architecture through production operation.
Location: Remote in the U.S.; San Jose office (HQ). Preference for candidates based in the Bay Area.
Salary: $200K–$250K plus equity.
Company
builds multi-agent AI systems that automate complex enterprise workflows across platforms including SAP, Salesforce, Workday, Snowflake, and MuleSoft.
What you will do
- Build core data platform services and APIs for data access, query execution, ingestion, and synchronization.
- Develop reusable connector frameworks and abstractions for different enterprise systems and data access patterns.
- Improve query and data-movement performance through partitioning, parallelism, and effective memory and storage management.
- Build orchestration, retries, checkpointing, and observability to support reliable recovery and data correctness.
- Work with product and engineering teams to define interfaces, make architectural tradeoffs, and operate capabilities in production.
Requirements
- At least 2+ years of experience as a Data Platform Engineer.
- Strong Python and SQL skills, with experience building maintainable, tested production software.
- Experience developing backend services, data infrastructure, or data platform components beyond configuring pipelines.
- Solid understanding of relational databases, query optimization, data formats, and the tradeoffs between querying data in place and materializing data elsewhere.
- Experience with concurrent or distributed workloads, including failure handling, resource management, and performance debugging.
- Ability to investigate unfamiliar systems and turn complex requirements into clear, practical designs.
Nice to have
- Experience with analytical query engines, lakehouse technologies, workflow orchestration, enterprise-system integrations, or containerized infrastructure.
- Experience building connector libraries, developer-facing APIs, or shared platforms used by other engineering teams.
- Familiarity with AWS, Azure, or GCP, including networking, storage, identity and access management, and infrastructure as code.
Culture & Benefits
- Build AI products addressing complex, real-world enterprise problems.
- Work at the intersection of AI, ERP systems, and automation.
- High ownership, high impact, and direct influence on product direction.
- Collaborate with a deeply technical and customer-focused team.
- Full-time remote work in the U.S.; San Jose office headquarters.
- Equity offered in addition to the stated compensation.
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