Senior Analyst Engineer - Intelligence Management

At Feedzai, we're building a world of safer money. A world where financial institutions move faster than criminals. Where the payments that fund real lives through salaries, savings, and businesses are protected in real time.

We use trusted AI to detect and prevent financial crime, fraud, and money laundering at scale: the world's top banks, payment networks, and acquirers trust our technology to safeguard more than one billion consumers and $9 trillion in payment volume every year.

Feedzai is a Series D company and has raised $282M to date. With a valuation of $2 billion, our technology protects 1 billion consumers and 90 billion transactions each year.

The Product Operations team exists to make Product demand absorbable at scale - predictable, sustainable, and governed by a clear operating system, so the business can expand without growing chaos. We run on three principles: intelligence over reporting, flow over heroics, and governance over guesswork.

Intelligence Management is the layer that turns signals into decisions. We instrument the operating system with data, automation, and AI - surfacing risks, opportunities, and pace deviations, and delivering insight that leaders consume directly, without routing a request through an analyst. We move value down the decision lifecycle - Data Dashboard Insights Intelligence Action - and remove manual toil from the loop, concentrating human judgement where it matters the most.

You:

You are a highly autonomous, technically credible professional who turns messy operational reality into trustworthy intelligence that leaders and teams act on.

You own and define the approach for ambiguous, high-impact problems - from "what is actually happening across the roadmap?" to automate this loop end-to-end.

You build the signals, systems, and automated insight that strengthen decision quality and speed, partnering, influencing, and challenging senior leaders with evidence so the department meets its yearly goals with margin instead of heroics.

You have a good financial acumen and are familiar with ROI metrics.

Your Day to Day:

In this role, you will autonomously partner with and challenge Product leaders (Directors and above), using data and automation to accelerate decisions and reduce the manual overhead of running the department and create intelligence. You will lead end-to-end or advise according to context, from initial problem framing through to sustained adoption. Your work centers on three pillars:

Intelligence Builder – turning signals into decisions

Design, build, and operate the signals, dashboards, and automated insights that leaders consume directly - without routing a request through an analyst or ops person.

Own data quality and trust: every number is accurate and traceable, with documented calculation logic. The intelligence layer is only as credible as the data beneath it.

Make monitoring self-serviceable - roadmap progress, goal execution, and risk emergence surfaced by default, with human oversight reserved for genuinely complex cases.

Pair closely with Engineering on upstream instrumentation, defining what data matters and what problems it must solve.

Decision Partner – challenging and enabling leaders

Translate operational data into decision-ready narratives for senior leadership forums: what is happening, what it means, and what decision it calls for.

Challenge Product Managers, Engineering Managers, and Senior Leadership with evidence when the data contradicts intuition, acting as a neutral third party in the debate.

Map and provide the insights that support investment and capacity trade-offs, using historical productivity and capacity data as reference.

Partner with Delivery Operations and Organizational Effectiveness so intelligence flows into the operating rhythm and the leadership narrative, rather than sitting in a dashboard.

Automation Force Multiplier – removing toil, reclaiming judgment

Roll out AI and agentic workflows that trigger alerts and action requests to the right individuals, plus push/pull context systems filtered by audience.

Automate governance and reporting workflows with measurable ROI in hours reclaimed.

Set standards and best practices for AI‑assisted analytical work, modelling AI‑first ways of working for the wider team to follow.

You Have & You Know-how:

5-7 years in data/analytics, decision intelligence, analytics engineering, or a similar role with direct engagement with senior stakeholders, ideally in fast-paced B2B Engineering/Product environments.

Strong hands‑on data skills: performant SQL and Python (Pandas), data modelling, pipelines/ETL, and building self‑service data products - comfort turning messy inputs into trustworthy signals.

Demonstrated ability to

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