Senior Data Engineer

Role: Data Engineer
Focus: Azure Cloud & Modern Data Engineering
Location: Remote / Hybrid / On‑site

Overview

We are looking for an experienced Data Engineer with strong expertise in Microsoft Azure to design, develop, optimize, and maintain scalable data pipelines and cloud-based data platforms. This role is ideal for someone who combines solid engineering skills with deep knowledge of Azure data services, automated data processing, and modern data architectures.

The ideal candidate will work closely with Data Architects, Data Scientists, BI engineers, and cross-functional development teams to ensure high-performance, reliable, and secure data ecosystems. This role requires hands-on experience in Azure-based data ingestion, transformation, storage, and orchestration.

Responsibilities

• Design, build, and maintain end-to-end data pipelines and ETL/ELT processes using Azure data services.

• Develop scalable data workflows leveraging Azure Data Factory, Databricks, Synapse Analytics, Azure Functions and related tools.

• Implement and optimize data storage solutions in Azure Data Lake Storage (ADLS), Azure SQL, Cosmos DB or similar.

• Build reliable ingestion layers using Azure Event Hubs, Azure Service Bus, Kafka or API-based integrations.

• Develop and maintain data models, curated datasets and data warehouse layers.

• Ensure data quality, consistency, and reliability by implementing data validation, monitoring, and automated testing.

• Optimize data pipelines for scalability, cost efficiency, and performance across Azure services.

• Collaborate with cloud engineering teams to apply best practices in infrastructure-as-code (IaC) using tools like Terraform or Bicep.

• Implement secure data governance principles, including data lineage, access control, and compliance.

• Work in Agile/Scrum environments, contributing to sprint planning, estimations, and technical documentation.

Required Skills & Experience

• Proven experience as a Data Engineer, preferably in cloud-native environments.

• Strong hands-on experience with the Azure ecosystem, ideally including:

  • Azure Data Factory (ADF)

  • Azure Databricks (Spark, PySpark, Scala or Python)

  • Azure Synapse Analytics

  • Azure Data Lake Storage (ADLS)

  • Azure Functions / Logic Apps

  • Azure SQL / SQL Data Warehouse

• Solid experience designing and implementing ETL/ELT pipelines and data transformation processes.

• Proficiency in at least one programming language: Python, Scala, SQL.

• Strong understanding of data modelling, including dimensional modelling and data warehouse principles.

• Experience working with big data frameworks (Spark, Delta Lake, Parquet).

• Knowledge of CI/CD pipelines and automation using Azure DevOps or GitHub Actions.

• Familiarity with IaC tools (Terraform, Bicep, ARM Templates).

• Understanding of data governance: data quality, cataloging, lineage.

Nice to Have

• Experience with Kafka, Event Hubs, or other streaming technologies.

• Knowledge of Machine Learning pipelines, MLOps or integration with Azure ML.

• Experience with container technologies (Docker, Kubernetes).

• Certification such as:

  • DP‑203: Azure Data Engineer Associate

  • AZ‑900, AZ‑104, or Databricks certifications.

Soft Skills

• Strong analytical and problem-solving capabilities.

• Ability to collaborate across multi-disciplinary teams.

• Proactive mindset with ownership of tasks and deliverables.

• Excellent communication and documentation skills.

This is an hybrid position twice in a month - in the office in Porto