Analytics Engineer: Finance Metrics & Data Lakehouse

Onmo; England; On-site; GBP 65,000 - 95,000; Full time

Job summary

Onmo is hiring an Analytics Engineer to own the business-ready layer of our Databricks lakehouse. You will translate credit policy and finance rules into trusted numbers, maintaining dimensional models and governed metrics used by Finance, Credit Risk, Collections and Operations.

You will define metrics, build Genie agents, and implement data quality checks while deploying with CI/CD and Databricks Asset Bundles. Comfortable bridging engineering and finance is essential.

Qualifications

• 2–4 years analytics engineering experience in production.
• Background in consumer credit, lending, cards or banking.
• Strong SQL and Python experience.
• Hands-on dimensional modelling and semantic/metrics layer work.
• Experience with a modern cloud data platform (Databricks preferred), Git and CI/CD.
• Comfortable deploying and scheduling work: workflow orchestration and code-based deployment.

Responsibilities

• Build and extend our gold-layer dimensional models, including point-in-time and month-end facts.
• Define and maintain governed metric definitions for credit and finance KPIs so all dashboards use the same numbers.
• Translate credit policy into tested SQL and reconcile against the general ledger and legacy reports.
• Build Genie agents over certified, documented datasets.
• Implement data quality checks, reconciliations and alerts around outputs.
• Deploy and operate what you build: orchestration, environment promotion and CI/CD via Databricks Asset Bundles.

Skills

SQL

Python

Dimensional modelling

Data governance

Databricks

CI/CD

Tools

Git

Terraform

Databricks Asset Bundles

Job description

Onmo is hiring an Analytics Engineer to own the business-ready layer of our Databricks lakehouse. You will translate credit policy and finance rules into trusted numbers, maintaining dimensional models and governed metrics used by Finance, Credit Risk, Collections and Operations.

You will define metrics, build Genie agents, and implement data quality checks while deploying with CI/CD and Databricks Asset Bundles. Comfortable bridging engineering and finance is essential.