Senior Data Engineer

TL;DR

Senior Data Engineer (Python/PySpark): Build and scale robust data solutions including high-performance pipelines for extraction, loading, transformation, and orchestration with an accent on scalability, reliability, and maintainability. Focus on championing modern practices like CI/CD, infrastructure-as-code, containerization, rigorous testing, monitoring, and collaborating with stakeholders to deliver production-ready systems.

LATAM (Remote)

What you will do

• Build, scale, and maintain robust data solutions.
• Implement and optimize high-performance data pipelines designed for scalability, reliability, maintainability, and speed.
• Champion modern software engineering practices including CI/CD, infrastructure-as-code, containerization, and cloud-native deployments.
• Collaborate with business stakeholders to transform use cases into production-ready services and solutions, owning systems from concept to production.
• Implement rigorous testing and monitoring practices to ensure data quality and integrity.

Requirements

• Bachelor's degree or higher in a STEM field (Computer Science, Math, Physics, or engineering preferred)
• 5+ years of experience in data engineering or related discipline
• Expertise in Python and SQL for data manipulation and analysis
• Proficiency with Databricks/PySpark and dbt for data warehousing and transformation
• Experience with workflow orchestration tools (e.g., Airflow, Dagster)
• Experience designing and implementing complex data systems, handling large-scale data projects including ETL and information retrieval
• Excellent communication skills, both verbal and written

Nice to have

• Experience with large language models (LLMs), prompt engineering, RAG, vector databases
• Knowledge of machine learning principles, feature engineering, knowledge graphs