About Codat
Codat is an advisory intelligence solution purpose-built for modern commercial banking. Through rich, specialized data, forward-looking insights, and integrated workflows, Codat empowers banking teams to deepen their relationships, grow their revenue, and simplify their day-to-day work.
Founded in 2017 and backed by JPMorgan, PayPal, Amex, Plaid, and Shopify, Codat has successfully powered over 350,000 connections to business customers’ financial systems — and is trusted by industry leaders to turn scattered information into actionable, strategic advantages in real time, every time.
The RoleWe're looking for a Senior Data Engineer to join our Insights team. You'll be hands-on every day — writing production code, building and maintaining data pipelines, and shipping features that turn raw data into actionable intelligence for our clients. You'll work across the full project lifecycle, from understanding the problem through to delivery, and you'll care as much about code quality and operational reliability as you do about getting things shipped.
This isn't a platform architecture role. You'll be building and owning pipelines end-to-end, not designing abstractions for other engineers to build on. You'll thrive if you're motivated by solving real user problems and you want to work somewhere your code has direct, visible business impact.
What You'll DoWrite production code daily, most likely in Python, building and maintaining the data pipelines that power our Insights products.
Own the full lifecycle of your projects: understanding the data domain, designing pragmatic solutions, shipping them, and keeping them running reliably.
Drive technical quality through strong engineering practices — testing, observability, data quality checks, and clean, maintainable code.
Collaborate with product, data science, and engineering stakeholders to shape what we build and how we build it.
Identify opportunities to apply AI within our products and workflows where it delivers genuine value.
Contribute to the growth of the team by sharing knowledge and championing good engineering practices.
Strong software engineering fundamentals: you write well-tested, production-ready code and care about maintainability, observability, and operational excellence.
Solid experience with modern data engineering tools and patterns — some combination of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and DBT.
Proficiency in a strongly typed language, ideally Python or C#.
Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud-based infrastructure.
A product mindset — you want to understand the business domain and use that understanding to influence what you build, not just how you build it.
The ability to communicate clearly with both technical and non-technical colleagues.
