Data Engineer, Product

Accountabilities:

• Design, build, and maintain scalable ETL/ELT data pipelines that transform raw data into high-quality datasets for machine learning and product use cases.


• Develop and optimize data transformation workflows supporting feature engineering for both offline model training and online inference systems.


• Collaborate closely with ML Engineers to understand data requirements and deliver reliable inputs for recommendation systems and predictive models.


• Ensure strong data quality, governance, and monitoring across all pipelines to guarantee accuracy, reliability, and consistency of datasets.


• Own data pipelines end-to-end, including design, implementation, deployment, monitoring, and continuous improvement.


• Improve performance, scalability, and efficiency of large-scale data processing systems, including batch and near real-time workloads.


• Contribute to building robust data foundations that enable experimentation, personalization, and ML-driven product innovation.

Requirements

• 5+ years of experience in Data Engineering or a similar role within data-intensive or product-driven environments.


• Strong hands-on experience with Apache Spark and Python for large-scale data processing and transformation.


• Solid knowledge of SQL and experience designing and working with data models and transformation logic.


• Proven experience building and maintaining ETL/ELT pipelines with end-to-end ownership.


• Experience working with high-volume data systems, including batch and/or near real-time processing pipelines.


• Strong ability to collaborate with Machine Learning and product teams in ML-driven environments.


• Familiarity with Databricks is a plus.


• Experience with streaming technologies (e.g., Kafka, Flink), feature stores, or ML data workflows is highly desirable.


• Strong problem-solving mindset with attention to scalability, performance, and data reliability.

• Competitive salary aligned with senior data engineering market standards (€64,800–€74,400 annually referenced in original posting)


• Employee stock option program


• Performance-based bonuses and referral rewards


• Flexible remote-first working model with location autonomy


• Personal learning and professional development budget


• Additional paid leave options


• Paid volunteering opportunities


• Opportunity to work remotely while traveling


• High-growth environment focused on product innovation and ML-driven systems

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