Submeter

Senior Data Engineer

Porto

Descrição da posição

We are looking for a Senior Data Engineer for a hybrid project, 4 days on-site per week, in Porto.

About the Role

You will be joining a specialised financial index team responsible for creating and licensing indices across Equity and Fixed Income asset classes. The team operates its own Python-based data infrastructure and works across two hubs: a Paris-based senior development team and a growing Porto-based team that you will be part of.

The business team is composed of financial and quantitative engineers who design index methodologies and write initial logic in Python notebooks. Your role is to take that notebook-level logic and translate it into clean, robust, production-grade Python pipelines with proper data flows, monitoring, quality controls and alerting.

This is a pure data engineering role.

Candidates with backgrounds primarily in backend development, AI/ML, BI reporting or chatbot development are not suitable for this position.

The Porto team is small and the role demands a high degree of autonomy. Developers take end-to-end ownership of projects from requirement gathering through to production deployment, often working independently. An entrepreneurial, self-sufficient mindset is essential.

Main Responsibilities

Translate index methodology logic and notebook-level Python code from the financial engineering team into clean, robust, production-ready pipelines.
Design and implement scalable data processing flows covering ingestion, transformation, aggregation, validation and monitoring.
Build data quality checks, alerting layers and monitoring into every pipeline to ensure production reliability.
Conduct peer code reviews and uphold engineering standards across the team.
Work directly with the financial engineering business team to gather requirements and understand index methodologies.
Take end-to-end ownership of projects, from initial requirements through to production deployment and monitoring.
Produce comprehensive technical documentation for all delivered solutions.
Work autonomously within a small, senior team with minimal process overhead.

Requirements

Confirmed hands-on Python experience in a production data engineering context, with a focus on data pipeline engineering (not backend, application or AI/ML development).
Demonstrated track record of building and owning end-to-end production data pipelines: ingestion, transformation, validation, monitoring and alerting.
Confirmed production experience with at least one of the following: Apache Airflow, Apache Spark or Kafka.
Strong SQL for data querying and validation.
Ability to work autonomously in small senior teams with full project ownership and minimal supervision.
Comfortable collaborating directly with non-technical business stakeholders to translate requirements into engineering solutions.

Nice to Have

Experience with Dataiku DSS.
Financial or quantitative domain background.
Knowledge of data quality and validation practices.

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