Principal Data Engineer - Real-Time Financial Crime Platform

Complyadvantage; Lisboa; Híbrido; EUR 92 000 - 115 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Equity

Unlimited Time Off

Hybrid work model

Home office budget

Learning budget

Resumo da oferta

ComplyAdvantage Lisbon is seeking a Principal Data Engineer to lead the design and evolution of the data platform powering our AML/KYC and fraud products. You will set the medium to long term direction for data infrastructure, partner with Engineering, Data Science, Product and SRE leaders, and coach engineers across the organisation.

Your work will shape data foundations that support ML, feature stores and real-time signals, ensuring scalable, well-governed pipelines and a knowledge graph that

Qualificações

• Experience designing production-grade data platforms at scale.
• Strong Python production experience; Java/Kotlin能力 for direction.
• Experience with cloud (AWS/GCP) and containerised infra (Kubernetes).

Responsabilidades

• Own the data platform architecture behind sanctions, AML, KYC, fraud and risk products.
• Lead architecture for ML and data science integration; ship models and signals rapidly.
• Define data quality, observability, contracts and lineage standards.
• Coach engineers across tribes and represent engineering externally at events.
• Build APIs and event streams; drive documentation for self-serve usage.

Conhecimentos

Data platform architecture

Distributed data systems

Python

Java/Kotlin

Cloud (AWS/GCP)

Kubernetes/Docker

Data quality & observability

Technical leadership

Coaching engineers

Documentation writing

Ferramentas

Kafka

dbt

ArgoCD

Spark/Flink

Postgres/Yugabyte

REST/gRPC

Descrição da oferta de emprego

ComplyAdvantage Lisbon is seeking a Principal Data Engineer to lead the design and evolution of the data platform powering our AML/KYC and fraud products. You will set the medium to long term direction for data infrastructure, partner with Engineering, Data Science, Product and SRE leaders, and coach engineers across the organisation.

Your work will shape data foundations that support ML, feature stores and real-time signals, ensuring scalable, well-governed pipelines and a knowledge graph that