Data Engineer, Product

About Eneba

At Eneba, we’re building an open, safe and sustainable marketplace for the gamers of today and tomorrow. Our marketplace supports close to 20m+ active users (and growing fast!), provides a level of trust, safety and market accessibility unparalleled to none. We’re proud of what we’ve accomplished in such a short time and look forward to sharing this journey with you. Join us as we continue to scale, diversify our portfolio, and grow with the evolving community of gamers.

About The Team

We are a mobile application where users earn rewards by playing games. Our Data Engine team is at the heart of this ecosystem, working in a high-impact environment to build the recommendation systems and ML models that drive our product's growth. You will join a specialized squad of Data and ML Engineers focused on optimizing user journeys and scaling our platform toward full profitability. We are a lean, high-ownership team where every engineer manages their pipelines from A to Z.

What It’s Like To Work At Eneba

• Opportunity to join our Employee Stock Options program.
• Opportunity to help scale a unique product.
• Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.
• Paid volunteering opportunities.
• Work location of your choice: office, remote, opportunity to work and travel.
• Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes.
• Please attach CV's in English.
• 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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.