Participate in cross-functional meetings to define project objectives and scope.
Analyze and prioritize business requirements related to data.
Design and develop data extraction, transformation, and loading pipelines (ETL/ELT).
Develop applications for extracting data from various sources and formats (JSON, XML, PDF, etc.).
Write clean, efficient, and scalable code, adapting to new technologies as needed.
Implement data quality methodologies throughout ingestion and transformation processes.
Optimize services, queries, and processes to reduce operational costs and improve performance.
Validate the functionality, integrity, and security of data engineering processes.

Bachelor’s degree in Computer Systems Engineering, Computer Science, or related field.
Specialization in Data Engineering (preferred).
5 to 8 years of experience in similar roles.
Hands-on experience with batch and streaming data processing.
Intermediate-Advanced English proficiency.
Programming languages: Java, Scala, Python, and SQL.
Experience with data processing frameworks (Spark, Flink, etc.).
Knowledge of SQL and NoSQL databases (PostgreSQL, Cassandra, MongoDB, etc.).
Experience with orchestration and ETL tools (Airflow, Airbyte, Stitch, etc.).
Experience handling large-scale data transformations across multiple formats.
Design and architecture of Data Lakes, Data Warehouses, and Lakehouse solutions.
Data modeling (star schema, snowflake schema, OBT).
Development and consumption of REST APIs.
Agile methodologies and version control (Git).
Experience with web scraping projects (nice to have).
Knowledge of additional languages such as Go or JavaScript (nice to have).
Experience with streaming and messaging systems (Kafka, RabbitMQ) (nice to have).
Background in data science projects (nice to have).

Data Engineer

Key skills