Entry - Level Data Engineer at GM, focusing on building large scale data platforms in cloud environments. Collaborating with data engineers and scientists while migrating systems to cloud solutions.
About the role
- 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.
- Wellhub and TotalPass.
- Private pension plan.
- Childcare allowance.
- Health insurance.
- Dental care.
- Life insurance.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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