Senior Backend Engineer – Data Pipelines & AI (Remote)

TrulyHired; United States; Remote; USD 130,000 - 190,000; Full time

Job summary

GiveCampus is seeking two Senior Software Engineers to build scalable data pipelines that move millions of donor records between schools, CRMs, and partner apps. You will design robust AWS-based ETL flows, integrate with Blackbaud Raiser's Edge NXT, Salesforce-based systems, and a growing API ecosystem, all while shaping how AI agents are used in engineering practice.

You will own major components from day one, ensuring reliable synchronization, handling rate limits, and maintaining data

Qualifications

• 6+ years building and running production backend systems, including a distributed ETL or sync pipeline that moved tens of millions of records.
• Third-party API integration experience: auth, token expiry, rate limits, retries, and upsert semantics.
• Careful data modeling with external IDs, timezone-safe bulk writes, and safety of busy core tables.
• Excellent written communication; ability to write design docs and PR descriptions for a distributed team.

Responsibilities

• Design and ship AWS-based pipelines with idempotent consumers and throttling to keep CRM budgets intact.
• Reconcile records across file uploads, APIs, and CRMs like Raiser's Edge NXT and Salesforce-based systems.
• Build versioned, documented endpoints for partner APIs and ensure testing with OpenAPI and related tooling.
• Own large portions of the pipeline and mentor others in agent-enabled engineering practices.

Skills

ETL pipelines

APIs integration

AWS

Ruby on Rails

OpenAPI

PostgreSQL

RSpec

Data modeling

Tools

PostgreSQL

Redis

AWS

S3

SQS

New Relic

Sentry

Metabase

Job description

GiveCampus is seeking two Senior Software Engineers to build scalable data pipelines that move millions of donor records between schools, CRMs, and partner apps. You will design robust AWS-based ETL flows, integrate with Blackbaud Raiser's Edge NXT, Salesforce-based systems, and a growing API ecosystem, all while shaping how AI agents are used in engineering practice.

You will own major components from day one, ensuring reliable synchronization, handling rate limits, and maintaining data