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Element451

Integrations Architect

Posted 4 Days Ago
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Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Own integration delivery and reliability for higher-education customer implementations. Configure API and batch integrations, lead data mapping and governance, validate data quality, troubleshoot authentication and synchronization failures, and establish monitoring practices. Create reusable integration patterns, runbooks, and troubleshooting guides while coordinating with campus IT, implementation, customer success, support, product, and engineering teams.
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Integrations Architect

About Element451

Element451 is the AI-native CRM and agent platform built for higher education. We help colleges and universities modernize engagement, recruitment, enrollment, and student success with intelligent automation and a product customers genuinely love.

The Role

As an Integrations Architect, you own the integration workstream during implementation and support the reliability of data flows post-launch in partnership with CS and Support. You are the technical bridge between Element451 and campus IT — translating institutional system reality into mappings, validations, and repeatable integration setups.

You're not writing production code, but you are deeply technical: you test APIs, troubleshoot auth and sync failures, validate data integrity, and build the runbooks that prevent repeat issues.

What You'll OwnIntegration delivery (API + batch/flat-file)
  • Configure, validate, and launch integrations between Element451 and institutional systems (SIS/ERP/financial aid/3rd parties)

  • Implement and maintain batch workflows where APIs aren't available (SFTP, CSV specs, schedules, transformations/normalization, validation)

  • Partner with Implementation Leads to align integration timelines with go-live milestones and unblock dependencies early

Data mapping & governance
  • Lead mapping sessions with campus IT and functional stakeholders: field definitions, formats, transformations, and "system of record" decisions

  • Define data quality standards and validation checks so downstream workflows (automation, segmentation, reporting, AI agents) behave correctly

  • Document mappings, assumptions, and edge cases in a way that is usable for CS and Support post-launch

Troubleshooting & reliability
  • Diagnose integration issues using logs, error payloads, and testing tools (e.g., Postman)

  • Identify root cause across auth, endpoints, payload formatting, source data, or scheduling

  • Resolve issues independently where possible; escalate to Engineering only when required — with clear reproduction steps, impact, and artifacts

  • Establish monitoring habits and proactive checks to catch failures before customers report them (no silent failures)

Cross-functional enablement & scale
  • Build and maintain integration runbooks, troubleshooting playbooks, and "known failure modes" guides

  • Create reusable integration patterns for common higher-ed ecosystem combinations to reduce time-to-go-live

  • Surface recurring issues and integration friction as structured signals to Product/Engineering (patterns, not anecdotes)

What You'll Bring
  • 3–6 years in integrations, technical support, data operations, implementation engineering, or similar roles with APIs as a core responsibility

  • Strong REST/API fundamentals: reading docs, testing endpoints, debugging, handling errors, pagination, rate limits

  • Comfortable with auth patterns (OAuth2, API keys, tokens) and common failure modes

  • Experience with SFTP/CSV/batch integration workflows and rigorous mapping/validation practices

  • Working familiarity with higher-ed SIS/ERP concepts and terminology; experience with systems like Banner, Colleague, PeopleSoft, Workday Student, Jenzabar, etc. is a plus

  • Strong written communication — clear for campus IT and precise for internal teams

How We Measure Success
  • Integration go-live success: integrations launch on schedule without blocking go-live

  • Integration health: fewer silent failures, stale syncs, and recurring data quality issues

  • Time-to-resolution: faster recovery when issues occur

  • Engineering escalation rate: high % resolved without Engineering involvement

  • Documentation coverage: mapping docs and runbooks are complete, current, and actually used

  • Scalability impact: reusable patterns reduce time-to-go-live over time

What This Role Is Not
  • Not a software engineering role (you won't build production features)

  • Not a generalist implementation role (integrations are the core responsibility)

  • Not passive ticket triage — you prevent repeats and improve reliability

  • Not documentation-optional — if it isn't documented, it doesn't scale

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