Data Engineer: Build Scalable Pipelines & Insights (Hybrid)

BI4ALL; Porto; Hybrid; EUR 48,000 - 72,000; Full time

Benefits offered by this job

Competitive compensation

Hybrid and flexible working model

Tailored learning paths

Brand-new offices with perks

Focus on work-life balance

Job summary

A leading consulting firm in Porto is looking for a passionate Data Engineer to design and implement data architectures. You will develop pipelines and collaborate with teams to ensure data quality. Ideal candidates have 2-4 years of experience and proficiency in SQL, Python, and Microsoft Azure tools. This position offers competitive compensation, a hybrid working model, and various perks including a gym and flexible working conditions. Join us to make a significant impact in data-driven solutions.

Qualifications

• 2-4 years of hands-on experience in Data Engineering, preferably in a consulting environment.
• Mastery of Microsoft tools and services: Data Factory, Synapse Analytics, Databricks, Azure SQL and Fabric.
• Knowledge of ingestion tools and modeling tools.

Responsibilities

• Participate in the design and implementation of secure data architectures.
• Develop, improve and maintain data pipelines using Azure tools.
• Ensure data quality, traceability and consistency of information.

Skills

Data Engineering

SQL

Python

Spark (Databricks/Fabric)

DevOps

Agile/Scrum methodologies

Analytical skills

Communication skills

English proficiency

Tools

Azure Data Factory

Synapse Analytics

Databricks

Azure SQL

Fivetran

DBT

Airflow

Job description

A leading consulting firm in Porto is looking for a passionate Data Engineer to design and implement data architectures. You will develop pipelines and collaborate with teams to ensure data quality. Ideal candidates have 2-4 years of experience and proficiency in SQL, Python, and Microsoft Azure tools. This position offers competitive compensation, a hybrid working model, and various perks including a gym and flexible working conditions. Join us to make a significant impact in data-driven solutions.