Senior Data Engineer - AI-Driven Fintech (Hybrid)

Moneyfarm; Lombardia; Hybrid; EUR 45,000 - 65,000; Full time

Benefits offered by this job

Health insurance

Wellness plan

Fee-free investing

Structured onboarding

Career growth

Team events

Job summary

Moneyfarm, a pan-European digital wealth manager, is hiring a Senior Data Engineer. You will design and maintain data infrastructure (in ingestion, orchestration, and transformation), build analytical data models, and help decommission legacy components while ensuring data continuity.

You’ll collaborate with analysts, engineers, and product teams to deploy ML/AI applications, contributing to a data-driven culture.

Qualifications

• 5+ years of relevant work experience in data engineering
• Degree in Engineering, Computer Science or related discipline
• Experience in fintech / wealth management is a plus

Responsibilities

• Own the design, implementation, and maintenance of data infrastructure for ingestion, orchestration, and transformation
• Build and maintain analytical data models, ensuring they are performant, scalable, and reliable
• Contribute to decommissioning legacy components while ensuring data continuity
• Contribute to AI powered capabilities of Moneyfarm’s Data Platform
• Share best practices through code reviews and knowledge sharing
• Work closely with analysts, software engineers, and product teams to solve complex data problems and deploy ML/AI applications
• Promote data culture and best practices across the team

Skills

SQL

Python

Airflow

DBT

Redshift

AWS

Terraform

AI tooling

English fluency

Education

BSc or higher in Engineering/CS or related

Tools

BigQuery

Job description

Moneyfarm, a pan-European digital wealth manager, is hiring a Senior Data Engineer. You will design and maintain data infrastructure (in ingestion, orchestration, and transformation), build analytical data models, and help decommission legacy components while ensuring data continuity.

You’ll collaborate with analysts, engineers, and product teams to deploy ML/AI applications, contributing to a data-driven culture.