Data Engineer
Job Summary
Job Description
Eneba seeks a Data Engineer to create and maintain data pipelines, ensuring efficient data access. Collaboration with ML engineers is crucial for automating machine learning processes. The role involves building data infrastructure for analytics, hypothesis testing, and company metrics, optimizing data delivery, and improving data models. Responsibilities include designing and implementing process improvements and collaborating on large-scale data processing using Apache Spark and Python. Experience with Terraform, Git, SQL, and cloud platforms (AWS, Azure, Kubernetes) is essential.
Must have:
- 3+ years data engineering experience
- Proficiency in Terraform
- Extensive Apache Spark (Python) experience
- Git expertise
- Solid SQL knowledge
Good to have:
- AWS, Azure, or Kubernetes experience
- Databricks familiarity
Perks:
- Employee Stock Options
- Performance-based bonuses
- Referral bonuses
- Additional paid leave
- Personal learning budget
- Paid volunteering opportunities
- Remote work option
- Travel opportunities
11 skills required
Job Details
About Eneba
We’re building an open, safe and sustainable marketplace for the gamers of today and tomorrow. Our marketplace supports more than 10m+ 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're a Data team. We gather specialists passionate about data, our mission is to help grow Eneba organization as a data driven decision maker by providing a solid data foundation. We want to foster a healthy data culture across organization and enable our colleagues to have easier access to necessary data that they require in their day-to-day activities. Our team gathered ML experts who are creating amazing machine learning models. Data analysts provide crucial data insights for teams and data engineers who build cutting edge data pipeline solutions.
Responsibilities
- Enable efficient data access by creating and maintaining data pipelines.
- Collaborate with ML engineers to design and maintain automation for machine learning training, quality assessment, and model release process.
- Build data infrastructure from the vast amount of data for analytics, hypothesis testing and company metrics.
- Identify, design and implement improvement to internal processes allowing to optimize data delivery, automate manual processes.
- Design new and improve current patterns for building data models and implement necessary modifications.
Requirements
- 3+ years of experience in data engineering or in a similar role.
- Proficiency in Terraform for managing infrastructure as code.
- Extensive experience with Apache Spark using Python for large-scale data processing.
- Must have hands-on expertise with Git for version control and collaboration.
- Solid knowledge of SQL, essential for querying and managing relational databases.
- Experience with AWS, Azure, or other Kubernetes platforms is highly desirable.
- Familiarity with Databricks would be a significant advantage.
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
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