Data Engineer - Pipelines & ML Ops (Remote)

Eneba; United States; Remote; USD 100,000 - 160,000; Full time

Benefits offered by this job

Employee Stock Options

Personal learning budget

Volunteer opportunities

Job summary

Eneba is seeking a Data Engineer to build scalable data pipelines and models for a fast-growing gaming marketplace. You will collaborate with ML engineers to enable training, quality assessment, and model deployment, while shaping data infrastructure for analytics and key metrics.

5+ years in data engineering, Spark with Python, and cloud platform experience are required. This remote-friendly role offers opportunities for travel, Employee Stock Options, and a personal learning budget to grow

Qualifications

• 5+ years of experience in data engineering or a similar role.
• Extensive experience with Apache Spark using Python for large-scale data processing.
• Familiarity with Databricks or Snowflake would be a significant advantage.
• Experience with AWS, Azure, or other Kubernetes platforms is a huge plus.
• Must have hands-on expertise with Git for version control and collaboration.
• Solid knowledge of SQL, essential for querying and managing relational databases.

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.

Skills

Data engineering

Apache Spark

Python

SQL

Git

Cloud platforms (AWS/Azure)

Tools

Databricks

Snowflake

Job description

Eneba is seeking a Data Engineer to build scalable data pipelines and models for a fast-growing gaming marketplace. You will collaborate with ML engineers to enable training, quality assessment, and model deployment, while shaping data infrastructure for analytics and key metrics.

5+ years in data engineering, Spark with Python, and cloud platform experience are required. This remote-friendly role offers opportunities for travel, Employee Stock Options, and a personal learning budget to grow