Data Engineer - Modern Data Platform & BI (Hybrid)

Ayming; Lisboa; Hybrid; EUR 52,000 - 68,000; Full time

Benefits offered by this job

Meal allowance

Transport reimbursement

Private health insurance

Flexible hours

Hybrid work (60% remote)

Modern Sete Rios office

Job summary

Ayming in Lisbon is hiring a Data Engineer to drive our company-wide Data & AI transformation. You will design, implement, and scale a modern data platform enabling analytics, BI, and future AI use cases across the organization.

You will work with Data, BI, and business stakeholders to build robust data pipelines, contribute to architecture, and deliver high-quality datasets to analysts and product teams. A hybrid work model and international exposure await.

Qualifications

• 3+ years of data engineering experience.
• Strong SQL and data modeling skills.
• Hands-on Python for data processing.
• Experience with Databricks and modern data stack.
• Familiarity with cloud ecosystems (Azure/AWS/GCP).
• Knowledge of CI/CD and version control for data workflows.
• Experience enabling analytics with BI teams.
• Focus on quality, reusability, and maintainability of data assets.

Responsibilities

• Build and maintain data pipelines using Databricks.
• Contribute to architecture and modeling of the enterprise data platform.
• Develop high-quality, well-tested transformation logic.
• Deliver trusted, documented datasets to analysts and product teams for BI.
• Optimize data workflows for scale, reliability, and cost efficiency.
• Help define engineering standards, best practices, and documentation.

Skills

Data engineering

SQL

Python

Databricks

Data modeling

Cloud platforms

CI/CD

BI collaboration

Tools

Databricks

Job description

Ayming in Lisbon is hiring a Data Engineer to drive our company-wide Data & AI transformation. You will design, implement, and scale a modern data platform enabling analytics, BI, and future AI use cases across the organization.

You will work with Data, BI, and business stakeholders to build robust data pipelines, contribute to architecture, and deliver high-quality datasets to analysts and product teams. A hybrid work model and international exposure await.