Systems Integration Engineer 2

Join us in bringing joy to customer experience.

Engineering Operations keeps the systems that plan and track our engineering work running and connected. We are hiring a Systems Integration Engineer to write the code that links those systems, so leaders see the same numbers wherever they look and nobody rebuilds a status report by hand.

About the role

Roadmap items sit in one tool and delivery work sits in another. Status reports get rebuilt every quarter. You will build the integrations that move this data on its own and keep it consistent.

The code serves a purpose. Our leaders use this data to decide where engineering capacity goes, which commitments are at risk, and what to stop doing. You will know which decision each integration supports and who makes it. If you can’t say, we shouldn’t build it yet.

You will work with engineering operations managers, engineering leaders, and tool administrators. This role has no direct reports. You own the integrations and answer for whether they work and whether people use them.

Key responsibilities

• Write the code that connects the systems Engineering Operations depends on. This means Python that calls APIs, parses responses, handles failures, and runs on a schedule or on events. No-code rules and workflow builders are not part of the job.
• Maintain the model that links roadmap items to delivery work, and fix mismatches when they appear, escalating design changes to a senior engineer.
• Ask what decision a request supports before you build it, and raise requests to automate reports nobody acts on.
• Monitor integrations, fix failures, and update the runbook so someone else can fix them next time.
• Build and maintain the automated feeds behind OKR, QBR, and capacity reporting, and cut the manual steps that produce them.
• Support reviews of new tools and connectors by gathering information on cost to run and impact on the people who use them.
• Document how each integration works and what data it moves.
• Help engineering operations team members use the tooling without breaking the data.

Requirements

• 2 to 4 years of experience building software that integrates systems, not configuring them.
• Python you can write and debug on your own. You have shipped scripts or services that other people depend on, and you can show the code.
• Working experience with REST APIs. You have handled authentication, pagination, rate limits, and retries, and you are learning how to handle partial failures.
• At least one integration between two systems that weren’t designed to work together, where you mapped mismatched data models.
• Working knowledge of the Jira or Confluence API and permission model, or a comparable work management platform.
• Business sense. You can explain why the company is investing in a system, what the people using it are trying to get done, and when the honest answer is that it isn’t worth building.
• Clear communication. You can explain a data problem to an engineering operations manager and a technical tradeoff to an engineering director.
• A habit of writing down how things work.

Preferred

• Experience working in an AI-driven development lifecycle (AI-DLC), meaning you use AI coding tools as a collaborator, review what they produce, and can tell good, generated code from code that only looks right.
• Experience with webhooks, queues, or event-driven integrations.
• Experience with a BI or reporting tool.
• Background in an engineering operations or program team.

What success looks like

• Quarterly reports come straight from the systems with no manual rework.
• Monitoring finds integration failures before users do.
• You can name the decision each integration supports, and you retire the ones nobody uses.
• A new engineering operations manager can learn the tooling from the documentation.