This is a fully remote position, open to applicants in Costa Rica.

• Design, develop, and maintain scalable, secure, and reliable data pipelines utilizing Databricks, Spark, and cloud-native technologies.

• Construct and enhance metadata-driven ETL/ELT pipelines.

• Integrate data from various internal and external systems into analytics-ready datasets.

• Support AI/ML and advanced analytics efforts by providing high-quality data assets.

• Implement data quality controls, monitoring, and validation frameworks.

• Troubleshoot data pipeline failures and resolve production-related issues.

• Optimize data processing performance to ensure operational reliability.

• Collaborate with Data Science, Analytics, Product, and Engineering teams.

• Create curated datasets for reporting and visualization platforms such as Tableau and Power BI.

• Offer technical mentorship and contribute to engineering best practices.

• Over 5 years of professional experience in Data Engineering.

• At least 3 years of hands-on experience with Databricks and Apache Spark.

• Advanced SQL proficiency, including complex transformations and query optimization.

• Extensive experience in designing and implementing ETL/ELT solutions.

• Familiarity with distributed data processing and streaming technologies such as Kafka, Kinesis, Hadoop, or Spark Streaming.

• Experience with ETL orchestration tools like Azure Data Factory, AWS Glue, Informatica, Talend, or IBM DataStage.

• Proven experience in supporting production environments, troubleshooting issues, and resolving data-related incidents.

• Strong communication and stakeholder management capabilities.

• Fluent English communication skills at a professional level.

• Opportunity to engage in innovative data and AI initiatives.

• Collaboration with global teams and exposure to industry-leading technologies.

• A dynamic and fast-paced environment that emphasizes innovation and continuous improvement.

Data Engineer

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