We are looking for a highly skilled Data Engineer to join our team. The professional will be responsible for designing, building, and maintaining scalable and efficient data pipelines, ensuring data quality, reliability, and accessibility to support strategic business decisions.

Responsibilities:

Data modeling, optimization, and extraction using SQL;

Development and maintenance of efficient and scalable data pipelines;

Handling and processing large volumes of data using Python;

Implementation and management of workflow orchestration tools;

Administration and optimization of relational and NoSQL databases;

Working with Big Data platforms such as Spark, Hadoop, and Databricks;

Utilizing cloud services, especially AWS, for data processing and storage;

Implementation and maintenance of data lakes;

Monitoring and optimizing pipelines to ensure high performance and scalability;

Deep analysis of data, its origins, and its impact on the business;

Handling semi-structured and unstructured data;

Applying data profiling techniques to ensure data quality and reliability;

Identifying and proposing improvements in data collection, organization, and governance processes.

Requirements:

Solid experience in data engineering;

Proficiency in SQL for data modeling and optimization;

Advanced knowledge of Python for data manipulation and processing;

Experience with data orchestration tools (Airflow, Prefect, Luigi, etc.);

Knowledge of relational and NoSQL databases;

Experience with Big Data platforms such as Apache Spark and Hadoop;

Familiarity with cloud services, especially AWS (S3, Redshift, Glue, EMR, among others);

Experience in implementing and maintaining data lakes;

Skills in data pipeline optimization and monitoring;

Knowledge of data profiling and data quality assurance;

Analytical ability to understand data origins and business impact;

Proactive in identifying and suggesting improvements in data engineering processes.

Preferred Qualifications:

Experience with data governance tools;

Knowledge of modern data architectures (Data Mesh, Data Fabric, etc.);

Experience with CI/CD for data pipelines;

Familiarity with machine learning techniques and data science.