Design and develop data products for deposits, loans, credit cards, and risk management, ensuring the reliability and scalability of your data solutions

Integrate data source systems and ensure data quality and consistency across multiple platforms

Develop and maintain data pipelines using Spark and Apache Airflow, optimizing performance and scalability

Design and optimize complex SQL queries and data models, ensuring efficient data retrieval and storage

Collaborate with cross-functional teams to understand business requirements and develop innovative data solutions

Participate in code reviews and ensure compliance with coding standards and best practices

Contribute to the development of automated testing frameworks and tools to ensure the quality of our data solutions

A minimum of 3 years of experience in Data Software Engineering, demonstrating expertise in designing and developing data products for large-scale applications

In-depth knowledge of Python programming and related libraries such as Pandas, PyTest, and Sonar, showcasing your proficiency in data manipulation and analysis

Expertise in Spark and Apache Airflow, highlighting your experience in building and maintaining data pipelines

Hands-on experience with AWS Big Data Services such as EMR, Lake Formation, and Glue, showcasing your ability to build scalable and reliable data solutions

Strong analytical and problem-solving skills, allowing you to identify and resolve complex data-related issues

Fluent spoken and written English at an upper-intermediate level or higher, enabling effective communication

Experience with GitLab and Docker, enabling you to build and deploy data solutions in a containerized environment.