Data Engineer building scalable cloud data pipelines in Azure and Databricks. Focus on Lakehouse architecture and data governance in a hybrid work model.
Responsibilities
Design and develop scalable, robust data ingestion and transformation pipelines on Azure and Databricks;
Build solutions based on Lakehouse architecture, organized into bronze, silver and gold layers;
Ensure pipeline performance and scalability through best practices in partitioning, caching and parallelism;
Automate processes with a focus on reusability, monitoring and quality control;
Act as a technical reference for the data engineering team, promoting best practices and standardization.
Requirements
Experience with transactional databases and requirements analysis;
Knowledge of Data Governance;
Strong familiarity with Azure Data Lake Gen2, Azure Data Factory, Key Vault and integration across Azure services;
Proficiency in Spark (PySpark) and Python for developing pipelines and transforming data;
Experience with Git and CI/CD practices applied to data pipelines;
Advanced conversational English.
Benefits
Multi-benefits card – choose how and where to use it.
Scholarships for undergraduate, graduate, MBA and language courses.
Certification incentive programs.
Flexible working hours.
Competitive salaries.
Annual performance review with a structured career plan.
Possibility of international career opportunities.
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