Nexus Cognitive

Nexus Cognitive

Staff Engineer

Remote - US · Staff+

Sponsorship not specifiedDetected 53 days ago
PythonJavaScalaSQLMachine LearningData EngineeringAgentic AILeadershipCommunicationMentoringPublic Speaking

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

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About the role

  • ABOUT NEXUS You don't have an AI story if you don't have your data story.
  • One identity, one governance envelope, one operational layer across every mainframe, data lake, warehouse, and streaming system in the business.
  • For the first time, enterprises can bring their existing stack along instead of rebuilding it - and still give AI agents full context across the estate.

Responsibilities

  • Define and drive the technical architecture and long-term roadmap for the company's data platform
  • Lead the design of large-scale, high-reliability data pipelines and systems spanning multiple teams
  • Set engineering standards for data modeling, testing, observability, and pipeline design across the organization
  • Partner with engineering, product, and analytics leadership to align data infrastructure investments with business priorities
  • Lead root-cause analysis for complex, cross-system data incidents and drive systemic fixes

Requirements

  • 7+ years of professional data engineering experience, including significant time designing large-scale data systems
  • Deep expertise in SQL and at least one programming language used for data engineering (e.g., Python, Scala, or Java)
  • Proven track record of setting technical direction and influencing engineering standards across teams
  • Extensive experience with cloud data platforms, data warehousing, and pipeline orchestration at scale
  • Strong communication skills, with experience presenting technical strategy to both engineering and business stakeholders

Nice to have

  • Track record of leading major platform migrations or re-architecture efforts
  • Experience with streaming architectures and real-time data processing at scale
  • Prior experience in a Staff, Principal, or equivalent individual-contributor leadership role
  • A collaborative team culture built on curiosity and respect
  • Challenging work where your contributions clearly matter
  • The opportunity to work at the intersection of cloud, data, and AI innovation
  • Familiarity with data governance, lineage, and compliance requirements
  • If this role sounds like a great fit - or even close to one - we'd love to hear from you.

Skills

  • That's where NexusOne comes in.
  • What we stand for is simple:
  • sovereign data, interoperable systems, decoupled intelligence - delivered the way modern software should be.
  • No rip-and-replace.
  • No multi-year transformation.
  • Our CEO Anu Jain puts it well:
  • 85+ open-source tools pre-integrated.
  • AI-native automations that deploy and self-heal the stack without human toil.
  • It's working, and fast.
  • Our platform processes credit risk data for 90%+ of US small businesses - 40M+ - every month.
  • Intent signals for 300M+ subscribers monthly for Africa's largest telco.
  • The data and AI layer for a Top 3 US bank.

Company info

  • https://www.youtube.com/watch?v=g8g50sv5GhQ
  • We're looking for a Staff Data Engineer to help set the technical direction for our data platform and mentor engineers across the organization.
  • This is a senior technical leadership role for someone who has built and scaled data systems before and wants to shape architecture, standards, and best practices at a company-wide level.
  • You'll partner closely with engineering leadership, analytics, and cross-functional stakeholders to ensure our data infrastructure can scale with the business.

This listing is sourced directly from Nexus Cognitive's careers page and normalized into a canonical job model.