Data Engineer

This is a fully remote position, open to applicants in Lithuania.

📋 Description

• Develop and sustain data pipelines that convert source data into dependable inputs for machine learning applications.

• Collaborate closely with ML engineers to assist in the creation and delivery of features for model training and inference processes.

• Enhance and refine data transformations utilized for feature generation, including pipelines that support both offline and online feature-related applications.

• Guarantee robust data quality assurance throughout pipelines by designing solutions that yield accurate, reliable, and well-monitored datasets.

• Take full ownership of pipelines from implementation to maintenance, while consistently enhancing performance, scalability, and efficiency.

⛳️ Requirements

• Over 5 years of experience in data engineering or a comparable role.

• Extensive hands-on experience in constructing ETL/ELT pipelines with accountability from design through maintenance.

• Strong proficiency in Apache Spark and Python, particularly for large-scale data transformation tasks.

• Good knowledge of SQL along with practical experience in working with data models and transformation logic.

• Experience with high-volume or frequently executing pipelines, including batch or near real-time processing contexts.

• Ability to work collaboratively with machine learning teams and comprehend data requirements in ML-driven environments.

• Familiarity with Databricks is a plus.

• Experience with streaming technologies (Flink, Kafka), feature stores, or ML-related data workflows is a significant advantage.

🏝️ Benefits

• Opportunity to participate in our Employee Stock Options program.

• Chance to contribute to scaling a distinctive product.

• Various bonus structures: performance-based bonuses, referral bonuses, additional paid leave, and a personal learning budget.

• Paid volunteering opportunities available.

• Flexible work location: choose to work from the office, remotely, or while traveling.

• Significant personal and professional growth supported by well-defined feedback and promotion processes.