Data Engineer — Hybrid Lisbon, Azure & Snowflake

Egor Group; Venda do Pinheiro; Hybrid; EUR 40,000 - 70,000; Full time

Benefits offered by this job

Meal allowance

Hybrid work model (Lisbon)

Other corporate benefits

Job summary

Egor Group, through its IT House partner, is seeking a Data Engineer for a logistics client in Lisbon. The role is hybrid, based in Lisbon with cross-team collaboration.

You will design and operate enterprise-grade ETL/ELT pipelines, integrate Azure and AWS data services, and work with Snowflake to deliver trustworthy data products. Fluent English is mandatory; collaboration with data scientists and IT teams is required.

Qualifications

• Strong experience with Python, SQL, data modelling and production data pipelines.
• Cloud-native data engineering on Azure with practical AWS exposure.
• Snowflake or similar cloud data platforms; data quality and governance.
• Collaborate with data scientists and IT teams; fluent English required.

Responsibilities

• Design, build, and operate ETL/ELT pipelines for analytics and AI use cases.
• Create reusable data products from various enterprise data sources.
• Implement data quality checks, monitoring, lineage, and governance patterns.
• Support integrations between Azure AI services, Snowflake, APIs, and data sources.
• Translate use cases into data models, pipelines, and serving layers.
• Onboard new data sources with data protection and access controls.

Skills

Python

SQL

Data modeling

ETL/ELT

Data pipelines

Azure

AWS

Snowflake

Data governance

Orchestration

Observability

Access management

Collaboration

GenAI tools

English proficiency

Tools

GitHub Copilot

Cursor

Job description

Egor Group, through its IT House partner, is seeking a Data Engineer for a logistics client in Lisbon. The role is hybrid, based in Lisbon with cross-team collaboration.

You will design and operate enterprise-grade ETL/ELT pipelines, integrate Azure and AWS data services, and work with Snowflake to deliver trustworthy data products. Fluent English is mandatory; collaboration with data scientists and IT teams is required.