Design, develop, and maintain ETL and data integration workflows using Apache Hop.
Extract data from multiple heterogeneous sources, transform data according to business rules, and load into target systems effectively.
Optimize ETL pipelines to improve performance and ensure data integrity.
Implement monitoring, error handling, and alerting mechanisms to maintain pipeline reliability.
Collaborate with data architects, analysts, and business stakeholders to gather and refine data requirements.
Leverage cloud platforms such as Azure and Databricks to build scalable data solutions.
Lead complex data engineering initiatives and provide technical guidance to peers.
Conduct code reviews and enforce best practices in data engineering and pipeline development.

Minimum of 6 years of experience in ETL development, data integration, or related data engineering roles.
Proven track record designing and maintaining complex data pipelines using Apache Hop or equivalent tools.
Experience integrating with data platforms including Kafka, Spark, and Hadoop.
Demonstrated expertise with cloud technologies, particularly Azure and Databricks.
Hands-on experience implementing workflow orchestration and automation using Airflow.
Experience leading technical initiatives and collaborating across multidisciplinary teams.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience.

Professional certifications in data engineering, cloud platforms, or ETL tools are advantageous.
Ongoing professional development through training, courses, or certifications is encouraged.
Flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

ETL Specialist, Apache Hop, Azure, Databricks, Kafka, Spark, Hadoop, Python, Airflow

Key skills