Senior Data Engineer

Reposted 2 Months Ago
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London, Greater London, England, GBR
Hybrid
Senior level
Fintech • Software • Financial Services
Through our API, financial service companies can access their small business customers' financial data more efficiently.
The Role
Build and maintain production data pipelines and systems in Python; lead technical direction for the Insights platform; improve engineering standards, observability, and data quality; apply AI across products and pipelines; help develop AI-ready data foundations such as semantic layers.
Summary Generated by Built In

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 Role

We're building the AI Assistant for commercial bankers. Relationship managers, treasury and credit teams use it to understand their business customers and act faster, and you'll be right in the middle of building it.

This is a hands-on job for people who like building and want to stay as an individual contributor. You'll design and ship the things the assistant depends on, and they'll still be yours once they're live. You'll also get a real say in where it goes next. That means making your case to engineers, product and the commercial team, and bringing them along with you.

What You'll Work On

  • The pipelines the assistant draws on, from raw source data to the numbers it quotes. You'll build them and keep them running.

  • The layers on top: metrics, definitions and the relationships between them, so a pile of financial data becomes something the assistant can reason over.

  • Testing and observability. We want what we ship to get more reliable, and we want the people around you to get better at it too.

You'll Probably Have

  • Built pipelines and production systems from scratch, writing the code yourself rather than mostly configuring managed services. If we ask about the hardest logic you've written, you'll have a story ready.

  • Good Python habits. Your tests are the kind someone else would be glad to inherit.

  • Real depth in a few of SQL, Spark, Databricks/Delta Lake, Dagster/Airflow/Temporal and dbt, and opinions about which ones annoyed you.

  • Time with CI/CD, Docker and cloud infrastructure. Even better if you set them up for a team.

  • An interest in the business behind the data. If the data says the request is wrong, you'll say so.

  • AI already built into how you work. You can show us where it saved you real time, or got you up to speed on something new.

  • Nice to have: some experience getting data ready for LLMs, like semantic layers, text-to-SQL or retrieval.

How We Work

We're a small team with plenty to do. Things move fast: we'd rather ship something useful and improve it than polish it in private. What you build is yours from start to finish.

There’s no return-to-office mandate, and you can work hybrid or fully remote. We trust you to be around when the team needs you and to deliver what you said you would. What we don’t want is anyone staying online late to prove a point.

Skills Required

  • Production-ready, well-tested Python development
  • Track record building data pipelines and production systems from the ground up
  • SQL
  • Spark
  • Databricks
  • Delta Lake
  • Dagster
  • Airflow
  • Temporal
  • dbt
  • CI/CD and modern deployment practices
  • Containerisation (Docker)
  • Experience with cloud-based infrastructure
  • Product mindset and ability to shape what gets built
  • Strong communication skills and ability to hold visible technical leadership
  • AI as a default way of working with evidence of practical usage and efficiency gains
  • Exposure to semantic layers, ontologies, text-to-SQL, or applying AI operationally within data platforms
Am I A Good Fit?
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The Company
HQ: London
211 Employees
Year Founded: 2017

What We Do

Our mission is to make life easier for the lifeblood of economies globally; small and medium-sized businesses. Codat is a universal API for consented business financial data, powering the next generation of products and services for this historically underserved market. We have offices in London, New York, San Francisco, and Sydney. We are a privately held company, and have recently closed our Series B funding and are funded by Index Ventures, Tiger Global, American Express, PayPal and a line-up of world class angel investors.

Why Work With Us

We are a people-first company that not only values our relationships with our clients and partners, but our internal employees as well. We promote from within and pride ourselves on creating a diverse, yet inclusive environment where we can collaborate, create, strategize, and grow together. We work hard, play hard, and win big.

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