Senior Data Engineer on Codat's Data and Insights team, building and operating data pipelines while setting technical direction for the Insights platform.
Responsibilities
- ▹Write production code every day, most likely in Python, building and maintaining data pipelines
- ▹Own the full lifecycle of projects, from understanding the problem through to delivery
- ▹Set and lead the technical direction of the Insights platform, communicating it openly across engineering and the business
- ▹Help raise engineering standards through testing, observability, data quality checks and clean, maintainable code
- ▹Make AI the default way of working, from research and prototyping through to operational uses such as agents that diagnose pipeline issues
- ▹Help lay the foundations for an emerging MCP and semantic layer so data becomes queryable by both people and AI systems
Requirements
- ▹Strong software engineering fundamentals: well-tested, production-ready Python
- ▹Track record of building data pipelines and production systems from the ground up
- ▹Solid experience with modern data engineering tools: SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), dbt
- ▹Comfort with modern deployment practices: CI/CD, containerization (Docker), cloud-based infrastructure
Soft skills
Clear, open communication of engineering decisions to product and business colleaguesHigh standards for code quality and operational reliabilityTechnical leadership with a hands-on mindset, staying close to the code
About the company
Codat is an advisory intelligence solution for modern commercial banking, delivering rich, specialized data, forward-looking insights and integrated workflows. Founded in 2017 and backed by JPMorgan, PayPal, Amex, Plaid and Shopify, it has powered over 350,000 connections to business customers' financial systems.
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