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Descrição
SteelEye is a fast moving RegTech (Regulatory Technology) start-up that is helping financial companies (e.g. banks, investment firms, brokers, hedge funds, and asset managers) meet their obligations under various global financial regulations.
Our work enhances financial compliance, prevents market abuse, and promotes trust in the financial markets.
Our people are passionate about leveraging data and technology to make this happen.
As a Data Integration Engineer, you’ll build and maintain Comms and Trades data ETLs—transforming raw client data into validated, searchable datasets that power the SteelEye platform.
You’ll deliver scoped integration work with regular guidance, collaborating closely with Engineering, Product, and internal integration stakeholders to ensure data arrives reliably and meets our schemas and quality standards.
Key responsibilities:
Build and maintain ETL/ET+L pipelines for communications and trades datasets, following established patterns and frameworks
Transform and validate incoming data to meet customer requirements and SteelEye’s internal data models/schemas
Develop in Python, using common data libraries (e.g., Pandas/Numpy) where appropriate
Implement and evolve Pydantic schemas and data mappings, ensuring consistency and testability
Orchestrate and Experience with other orchestrating frameworks such as Prefect, Temporal or Airflow is also valued.
Contribute to code reviews, improve code quality, and write clear technical documentation
Work cross-functionally with Product and other engineering teams to clarify requirements and resolve data issues
Troubleshoot ingestion issues and data quality problems; propose small, practical improvements
Use Jira/Confluence to manage work transparently and communicate progress and blockers early
Requirements
2–3+ years of relevant experience in a Python engineering / data engineering role
Strong Python fundamentals (clean, testable code; debugging; working with structured/unstructured data)
Comfortable working with schemas/validation (Pydantic ideal)
Familiarity with cloud and container tooling (AWS, Docker, Kubernetes)
Strong written and verbal communication; able to collaborate effectively across teams
Interview Process: The interview process is structured to assess candidates thoroughly across various competencies and skills relevant to the role.
Here's a description of each stage:
CV Review
Intro call with Human Resources Business Partner
First Stage Overview Interview with our Data Engineers
Final Interview with our Head of Data Engineering
Apply directly via: https://careers.steel-eye.com/jobs/7278917-data-engineer
Meteorologia no dia de início
sexta-feira, 6 de março — Parcialmente nublado · Máx 13° · Mín 8° · Chuva 23% (0mm) · Vento 20 km/h
Previsão para os dias seguintes
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sáb, 7 marParcialmente nubladoMáx 15° · Mín 5°
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dom, 8 marParcialmente nubladoMáx 16° · Mín 5°
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seg, 9 marAguaceirosMáx 11° · Mín 8°
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ter, 10 marParcialmente nubladoMáx 16° · Mín 7°
Detalhes
- Tipo de listagem
- Oferta de emprego
- Tipo horário
- Full-time
- Categoria
- Tecnologia
- Estado
- —
- Horário
- workflows using Conductor and Kubernetes
- Localização
- Braga, pt
- Início
- 06/03/2026
Salário de Mercado
€1 100 - €2 165/mês