Data Engineer

About the role

CRG Costa Rica is looking for an experienced Data Engineer to join a high-impact international project. The role focuses on designing, building and delivering scalable data solutions that enable analytics, business intelligence and AI-driven initiatives.

Key responsibilities

• Design, develop and maintain secure, reliable data pipelines using Databricks, Apache Spark and cloud-native technologies.
• Build and optimise metadata-driven ETL/ELT processes and integrate data from multiple internal and external sources.
• Support AI/ML and advanced analytics projects by providing high-quality, analytics-ready datasets.
• Implement data-quality controls, monitoring and validation frameworks, and troubleshoot pipeline failures.
• Optimise data processing performance and ensure operational reliability in production environments.
• Collaborate with Data Science, Analytics, Product and Engineering teams to deliver curated datasets for reporting tools such as Tableau and Power BI.
• Provide technical mentorship and contribute to engineering best practices.

Required profile

• 5+ years of professional experience in data engineering.
• 3+ years of hands-on experience with Databricks and Apache Spark.
• Advanced SQL skills, including complex transformations and query optimisation.
• Proven experience designing and implementing ETL/ELT solutions.
• Experience with distributed processing and streaming technologies (Kafka, Kinesis, Hadoop, Spark Streaming).
• Familiarity with ETL orchestration tools such as Azure Data Factory, AWS Glue, Informatica, Talend or IBM DataStage.
• Track record of supporting production environments, troubleshooting issues and resolving data incidents.
• Strong communication and stakeholder-management abilities, with professional-level English.

Required skills

• Databricks
• Apache Spark
• SQL
• ETL/ELT design
• Kafka
• Kinesis
• Hadoop
• Spark Streaming
• Azure Data Factory
• AWS Glue
• Informatica
• Talend
• IBM DataStage

What we offer

• Opportunity to work on innovative data and AI initiatives.
• Collaboration with global teams and industry-leading technologies.
• Dynamic, fast-paced environment focused on innovation and continuous improvement.