• Participate in the design, development, and enhancement of ETL processes
• Contribute to the development of the Data Platform and data models while ensuring accurate execution of daily tasks
• Develop new SQL queries and optimize existing ones
• Participate in building and improving new data models aligned with business requirements
• Create and maintain ETL data flows, monitor existing pipelines, identify and resolve issues proactively, and prevent recurring problems
• Contribute to the optimization of data flows and enhancement of data systems performance
• Support data platform and data security initiatives, collaborating with related teams to address identified gaps
• Participate in building data models aligned with data architecture and data security policies as part of becoming a data-driven organization
• Support internal AI, Data Governance, and Data Analytics teams on technical data-related matters and contribute to expanding data systems functionality

Data Processing & Transformation

• Practical experience with ETL and ELT principles, including batch and real-time data pipelines
• Strong Python skills for data processing, transformation, and automation
• Good knowledge and hands-on experience with SQL and PL/SQL, including query optimization
• Basic to intermediate experience with Apache Spark for large-scale parallel data processing
• Practical experience with DBT for building, modeling, and testing transformation pipelines

• Experience with Apache Airflow for workflow scheduling, orchestration, and automation
• Knowledge and hands-on experience with Apache Kafka and real-time data streaming fundamentals

• Knowledge of conceptual, logical, and physical data modelling
• Experience with Data Warehouse (DWH) concepts and modelling methodologies such as Kimball/Inmon and star/snowflake schema

• Practical knowledge of Docker and containerization principles
• Basic familiarity with Kubernetes and container orchestration

• Minimum 3 years of professional experience in data engineering and ETL/ELT implementation
• Hands-on experience building and managing SQL-based data pipelines using Apache Spark, Apache Airflow, and DBT
• Active participation in requirement analysis, technical solution development, and implementation of best practices within teams