Data Engineer

emagine; Lisboa; Híbrido; EUR 60 000 - 80 000; Tempo integral

Resumo da oferta

A leading technology consultancy in Lisbon is looking for a skilled Senior/Lead Data Engineer to develop cloud-native data pipelines, focusing on Microsoft technologies. The ideal candidate will possess strong knowledge of data architecture and mentoring fellow engineers. You should have proficiency in programming languages, experience with data lakes and warehousing, and a solid understanding of data management practices. The position offers a hybrid work model with 2 days in the office and 3 days remote.

Qualificações

• Strong background in cloud-native data pipeline development within Microsoft environments.
• Proven ability to implement high-performance data solutions.
• Strong knowledge of DevOps/DataOps practices including CI/CD.

Responsabilidades

• Develop and optimize data architectures and pipelines.
• Mentor mid/junior engineers and foster a collaborative culture.
• Translate complex decisions to non-technical stakeholders.

Conhecimentos

End-to-end data architecture and design

Cloud-native engineering (Microsoft)

Data warehousing and lake solutions

Python with data libraries

SQL

Spark

RDBMS knowledge

NoSQL databases

DevOps/DataOps practices

Data validation and monitoring

Ferramentas

Azure Data Factory

Azure Synapse

BigQuery

Azure Data Lake

Amazon Redshift

Descrição da oferta de emprego

We are seeking a skilled Senior / Lead Data Engineer with expertise in cloud-native data pipeline development within Microsoft environments. The ideal candidate will have a strong background in data architecture, data modelling, and the ability to implement high-performance data solutions that support our business objectives.

Technical Skills:

• Strong experience in end-to-end data architecture and design, including ingestion, modeling, storage, and orchestration (ex. Medallion).
• Proficiency in cloud-native engineering, with a focus on Microsoft technologies (Fabric, Azure Data Factory, Synapse) but open to other cloud platforms (AWS, Google Cloud) with comparable tools.
• Hands-on experience with data warehousing and data lake solutions (e.g., BigQuery, Azure Data Lake, Delta Lake, Amazon Redshift).
• Proficiency in programming languages such as Python (with data-related libraries: e.g. Pandas, Boto3), SQL, or Spark.
• Strong knowledge of RDBMS (e.g., Oracle, MS SQL Server) or NoSQL databases (e.g., MongoDB, ElasticSearch, GBQ).
• Experience with DevOps/DataOps practices, including CI/CD pipelines.
• Ability to implement data validation, lineage, documentation, and monitoring at scale.
• Proven ability to optimize pipelines and storage solutions for performance, cost, and reliability.

Soft Skills:

• Ability to evaluate trade-offs and make clear, defensible technical choices.
• Translate complex engineering decisions into clear, accurate explanations for non-technical stakeholders.
• Uplift and mentor mid/junior engineers, enforce standards, and foster a collaborative technical culture.
• Break down ambiguous, complex problems into clear, actionable steps and drive them to resolution.
• Take responsibility for outcomes, anticipate issues, and drive long-term platform evolution.
• Work model: 2 days per week in the office and 3 days at home.