Analytics Engineering Lead, Fincrime

Our Mission in Financial Crime & Fraud is to earn and keep our customers’ trust, support Monzo’s safe growth, and contribute to building a safer society. Data is crucial to the success of this mission and Analytics Engineers are the core of how we build and scale our data to Enable Monzo to Make Better Decisions, Faster, and help protect Monzo’s customers from Fraud and Financial crime.

At the core of this mission sits our data platform. We're great believers in powerful, real-time analytics and empowerment of the wider business. Every engineer at Monzo is responsible for collection of relevant analytics events from their microservices. We optimise for simplicity and re-usability – all our data lives in one place and is made available via our data warehouse in Google BigQuery. 90%% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.

What you’ll be working on:

As part of a multi-disciplinary data squad, you will have the opportunity to:

Serve as a data architect for Monzo’s Financial Crime and Fraud data, contributing to the design and scalability of data models that measure the effectiveness of fraud and financial crime controls.
Develop robust data models downstream of backend services, primarily in BigQuery, to support internal reporting, machine learning, as well as financial and regulatory use cases.
Help shape and maintain best practices for our Data Warehouse, including source data payload design, logical data modeling, implementation, metadata, and testing standards.
Collaboratively set standards and work with data across the Financial Crime and Fraud domain, fostering knowledge sharing and continuously improving data practices.
Contribute to prioritizsng data governance issues, ensuring a comprehensive approach to data integrity and compliance.

You should apply if:

You have a strong passion for data modeling, ETL projects, and Big Data, with experience as a developer or analyst.
You enjoy working with data streams from various services, such as financial, transactional, and operational systems.
SQL and data modeling are second nature to you, and you are comfortable with general Data Warehousing concepts.
You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others.
You have experience building robust and reliable data sets that require a high level of control.

The interview process:

Our interview process involves 3 main stages:

Initial Call
Take home task
Final Stage

Our average process takes around 2-3 weeks but we will always work around your availability.

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