Senior Engineering Intelligence Developer

At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.

What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.

Our customers rank among the who’s who in the Fortune 50. Coca-Cola, Linked In, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.

Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.

Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!

At Anaplan, we’re looking for a Senior Engineering Intelligence Developer to build the measurement engine behind Product and Technology. This is not traditional BI. It is a hands‑on, high‑trust role for someone who can turn engineering toolchain data into the metrics leaders use to improve delivery, quality, investment, adoption, and the future AI-augmented SDLC.

You’ll sit in Engineering Enablement and own the intelligence layer for how engineering work is understood. That means shaping DORA and value-stream measurement across Atlassian, Git Hub, CI/CD and adjacent tools; managing a KPI landscape of around 190 measures; and defining what we measure next as AI changes how software is planned, built, tested, and shipped.

We need a developer‑minded analytics specialist who can take an ambiguous leadership question, find the real problem, model the data properly, and create trusted self‑serve insight that lasts beyond the first dashboard.

• Own engineering intelligence end-to-end: raw data, modelling, semantic layers, dashboards, documentation, and the story behind the numbers.
• Build DORA metrics and value-stream measurement across Atlassian, Git Hub, CI/CD, and related engineering systems.
• Make sense of a KPI estate of around 190 measures spanning delivery, quality, dependency health, investment, and adoption.
• Define the next generation of SDLC metrics as AI changes how engineering work is planned, built, tested, and shipped.
• Advise when to build, buy, embed, or consume AI-enabled BI through Rovo, Atlassian Intelligence, Tableau/eazyBI, Power BI, and similar tooling.
• Turn broad questions from senior engineering leaders into clear, defensible, actionable answers.
• Contribute to engineering delivery through development tasks, data quality checks, and test data that improve completeness and confidence.
• Set the standards for definitions, governance, and modelling so Engineering Intelligence remains trusted as access broadens.

• Strong experience in reporting, BI, or analytics engineering within an Atlassian-heavy or comparable engineering toolchain.
• Deep SQL skills across warehouses with hundreds of tables, plus the judgment to turn complexity into usable models.
• Python capability for harder transformations, enrichment, automation, and data‑quality work.
• A track record of building semantic layers, governed definitions, and reusable models that outlast the person who built them.
• Practical familiarity with DORA, value-stream measurement, Dev Ops data, and CI/CD pipeline data.
• Hands‑on experience with eazyBI, Power BI, Tableau, or comparable BI platforms.
• Working knowledge of development practices and tools, including repositories, build tooling, scripting…