Ebury

2 weeks ago

Data Analyst - Financial Crime

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Join the Data Analytics & Anti-Money Laundering teams within Financial Crime to enable effective risk detection and operational efficiency. Design and maintain data models for transaction monitoring and customer risk assessment, deliver end-to-end FinCrime analytics (requirements, extraction, transformation, validation, deployment), optimize detection logic and monitoring rules, and build Sigma dashboards to support investigations and alert triage. Collaborate with investigators and compliance analysts to close data gaps and improve processes.

Location: Malaga, Madrid

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Design and maintain data models and datasets for transaction monitoring, customer risk assessment, and financial crime investigations.
•Own end-to-end delivery of FinCrime analytics solutions, including requirements gathering through deployment.
•Develop and optimize detection logic and monitoring rules for transaction monitoring scenarios, anomaly detection, and behavioural patterns.
•Perform data quality checks and controls to ensure completeness, accuracy, and auditability of FinCrime datasets.
•Build dashboards and analytical tools in Sigma to support investigations, alert triage, and risk assessment workflows.

Pay and Benefits

Perks:Health InsuranceGym Membership

Key Requirements

•2-4 years of experience in data/business analytics, preferably within FinCrime, Compliance, Risk, or Financial Services.
•Advanced SQL skills for reading and writing queries across complex datasets.
•Experience with modern data stack tools including dbt, Google Cloud BigQuery, Sigma, and Git (plus).
•Experience building data pipelines, transformations, and analytical datasets.
•Solid understanding of financial crime frameworks; Python experience is desirable.

Experience:2-4 yearsFinancial servicesAnti-money launderingFinancial crimeComplianceRisk

Skills:CollaborationAnalytical thinkingProblem-solvingData quality focusRisk interpretation

Languages:EnglishSpanish

Tech Stack:SQLDbtGoogle Cloud BigQuerySigmaGitPython

Company Brief

Ebury

Provides international payments, FX, and treasury solutions for SMEs and mid-market companies, enabling cross-border transactions, multi-currency accounts, and financing services to support global trade and cash flow management.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: London, United Kingdom

Founded: 2009

Website LinkedIn

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Ebury

2 weeks ago

Data Analyst - Financial Crime

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Malaga, Madrid

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Design and maintain data models and datasets for transaction monitoring, customer risk assessment, and financial crime investigations.
•Own end-to-end delivery of FinCrime analytics solutions, including requirements gathering through deployment.
•Develop and optimize detection logic and monitoring rules for transaction monitoring scenarios, anomaly detection, and behavioural patterns.
•Perform data quality checks and controls to ensure completeness, accuracy, and auditability of FinCrime datasets.
•Build dashboards and analytical tools in Sigma to support investigations, alert triage, and risk assessment workflows.

Pay and Benefits

Perks:Health InsuranceGym Membership

Key Requirements

•2-4 years of experience in data/business analytics, preferably within FinCrime, Compliance, Risk, or Financial Services.
•Advanced SQL skills for reading and writing queries across complex datasets.
•Experience with modern data stack tools including dbt, Google Cloud BigQuery, Sigma, and Git (plus).
•Experience building data pipelines, transformations, and analytical datasets.
•Solid understanding of financial crime frameworks; Python experience is desirable.

Experience:2-4 yearsFinancial servicesAnti-money launderingFinancial crimeComplianceRisk

Skills:CollaborationAnalytical thinkingProblem-solvingData quality focusRisk interpretation

Languages:EnglishSpanish

Tech Stack:SQLDbtGoogle Cloud BigQuerySigmaGitPython

Company Brief

Ebury

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: London, United Kingdom

Founded: 2009

Website LinkedIn