Data Engineer designing and developing data pipelines and infrastructure for processing and analyzing large data volumes at CIAL. Collaborating with data scientists to meet data requirements.
Responsibilities
Design and develop data pipelines to transfer, transform, and load data from various sources into a data warehouse or data lake.
Build and maintain the data infrastructure required for storing, processing, and analyzing data.
Develop and maintain data models for data storage, processing, and analysis.
Ensure data quality and integrity through data validation checks, data cleansing, and data profiling techniques.
Manage large volumes of data, including data storage, retrieval, and processing.
Collaborate with data scientists and analysts to understand their data requirements and provide the necessary data infrastructure.
Develop and maintain ETL workflows for moving data from source systems to data storage systems.
Optimize data performance by implementing indexing, partitioning, and other techniques.
Ensure data security by implementing data access controls, data encryption, and other security measures.
Stay up-to-date with emerging data technologies and industry trends to continuously improve data engineering processes and practices.
Requirements
Degree in Mathematics (statistics or financial) or Physics
Proficiency in Python (and Jupyter Notebooks)
Proficiency with ETL/ELT workflows
Familiarity with PostgreSQL and MongoDB
Good documentation writing skills
Good time-management skills
Good problem-solving skills
Attention to detail
English fluency is mandatory, Spanish and Portuguese a plus
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