Senior Analytics Engineer

Our Analytics Engineering discipline works in the intersection between data, engineering and our collectives - Money, Borrowing, Operations and Financial Crime and beyond. The team is responsible for building downstream data models from backend services with the desire to make our Data Warehouse a genuine competitive advantage for Monzo. We want a discipline capable of building an amazing Data Warehouse to support decision making, Business Intelligence, key financial reconciliation processes and best in class analytics and Data Science.

You'll be a senior individual contributor in our Analytics Engineering team, working across a variety of projects to spot patterns in the way we build our Data Warehouse and optimise our BI platform, Looker. You’ll help us minimise our cloud costs, drive best practices across all of our Data Discipline and scale and automate our data governance.

Enable Monzo to Make Better Decisions, Faster

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:

Working in a multi-disciplinary data / engineering squad, you will:

Support the building of robust data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases.
Focus on optimisation of our Data Warehouse, spotting opportunities to reduce complexity and cost.
Help define and manage best practices for our Data Warehouse. This may include payload design of source data, logical data modelling, implementation, metadata and testing standards.
Set standards and ways of working with data across Monzo, working collaboratively with others to make it happen.
Take established best practices and standards defined by the team, applying them within other areas of the business.
Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.
Contribute to prioritisation of data governance issues.

You should apply if:

You have experience and a passion for Data Modelling, ETL projects and Big Data as a developer or analyst.
SQL and data modelling are second nature to you
You are an comfortable with general Data Warehousing concepts
You strive for improvement in your work and that of others, proactively identifying issues and opportunities
You have experience building robust and reliable data sets requiring a high level of control

Nice to haves:

Any experience working within a finance function or knowledge of accounting.
Experience working in a highly regulated environment (e.g. finance, gaming, food, health care).
Knowledge of regulatory reporting and treasury operations in retail banking
Exposure to Python, Go or similar languages.
Experience working with orchestration frameworks such as Airflow/Luigi
Have previously used dbt, dataform or similar tooling.
Used to AGILE ways of working (Kanban, Scrum)

The Interview Process:

Our interview process involves 3 main stages:

First stage
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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