Company
Eneba jobs
4 active public jobs
Active public jobs
4 jobs
Compensation
*Salary ranges may vary. We’re seeking candidates with varied experience levels; from individual contributors to functional leaders in this space. *We’re an international team and our business language of choice is English. Good English level is required, proficiency is preferred. *To find out about how we handle your personal data, make sure to check out our Candidate Privacy Notice https://www.eneba.com/candidate-privacy-notice
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Responsibilities Build and maintain data pipelines that transform source data into reliable inputs for machine learning use cases. Work closely with ML engineers to support feature creation and delivery for model training and inference workflows. Develop and improve data transformations used for feature generation, including pipelines that feed offline and online feature-related use cases. Ensure strong data quality assurance across pipelines by designing solutions that produce accurate, trustworthy, and well-monitored datasets. Take ownership of pipelines end to end, from implementation to maintenance, while continuously improving performance, scalability, and efficiency. Requirements 5+ years of experience in data engineering or a similar role. Strong hands-on experience building ETL/ELT pipelines with ownership from design to maintenance. Solid expertise in Apache Spark and Python, especially for large-scale data transformation workloads. Good understanding of SQL and practical experience working with data models and transformation logic. Experience working with high-volume or frequently running pipelines, including batch or near real-time processing scenarios. Ability to collaborate effectively with machine learning teams and understand data needs in ML-driven environments. Familiarity with Databricks is an advantage. Experience with streaming technologies (Flink, Kafka), feature stores, or ML-related data workflows is a strong plus.
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