Lead Data Engineer: Data Pipelines & ML - Remote

Eneba; Spain; Remote; EUR 55,000 - 72,000; Full time

Benefits offered by this job

Employee stock options

Performance-based bonuses

Learning budget

Flexible remote work

Job summary

Eneba is building a scalable data-driven marketplace. We’re seeking a senior data engineer to create robust data pipelines and empower analytics across the business. You will work with ML teams to automate training, quality checks, and model releases while shaping data infrastructure for growth.

Join a data-driven culture with remote-friendly options, stock options, and a learning budget. 5+ years in data engineering, Spark with Python, and cloud platform experience are highly valued.

Qualifications

• 5+ years of experience in data engineering or a similar role.
• Experience with Apache Spark using Python for large-scale data processing.
• Familiarity with Databricks or similar cloud data platforms (Snowflake) is advantageous.
• Experience with AWS, Azure, or other Kubernetes platforms is a plus.
• Hands-on expertise with Git for version control and collaboration.
• Solid knowledge of SQL 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 ML training, quality assessment, and model release process.
• Build data infrastructure from large data sets for analytics, hypothesis testing and company metrics.
• Identify and implement improvements to internal processes to optimize data delivery and automate manual tasks.
• Design and improve data modeling patterns and implement necessary modifications.

Skills

PySpark

SQL

Data modeling

Git

Tools

Databricks

Snowflake

AWS

Azure

Kubernetes

Job description

Eneba is building a scalable data-driven marketplace. We’re seeking a senior data engineer to create robust data pipelines and empower analytics across the business. You will work with ML teams to automate training, quality checks, and model releases while shaping data infrastructure for growth.

Join a data-driven culture with remote-friendly options, stock options, and a learning budget. 5+ years in data engineering, Spark with Python, and cloud platform experience are highly valued.