Required experience:
— Education: Bachelor’s degree or higher in Computer Science, Information Technology, Data Science, or a related field.
Knowledge:
— Understanding of data modeling principles and practices;
— Data Warehouse, Data Lake concepts;
— ETL (Extract, Transform, Load) processes and tools for data ingestion, transformation, and processing;
— Design and develop data infrastructure;
— English — Intermediate.
Mandatory technical skills:
— Proficiency in programming languages: Python;
— Experience with database technologies: SQL, NoSQL, graph database
— Big data technologies: Spark, Kafka;
— Cloud platforms: Google Cloud Platform, including data services (Google BigQuery), storage management;
— Proficiency in version control systems: Git;
— Data pipeline orchestration tools: Apache Airflow or similar;
— Ability to optimize and tune database performance;
— Experience with data governance, security, and compliance practices;
— Documentation development, knowledge transfer.
Soft Skills:
— Strong problem-solving and analytical skills;
— Excellent communication skills to collaborate with cross-functional teams;
— Ability to work independently and in a team environment;
— Attention to detail and ability to work with large datasets efficiently;
— Adaptability to learn new technologies and tools quickly in a rapidly evolving field.
Preferred Qualifications:
— Industry certifications;
— Experience with machine learning frameworks and techniques, understanding MLOps approach;
— Knowledge of DevOps principles and practices for continuous integration and deployment (CI/CD);
— Experience with containerization and orchestration tools such as Docker and Kubernetes.
It will be a plus:
— Knowledge and experience of PHP