Data Engineer (Data Competency Center)

Requirements

• Proficiency in building, maintaining, testing, and delivering large-scale data pipelines
• ETL/ELT expertise: Practical experience with at least one end-to-end solution and its start, development, and maintenance
• Strong knowledge of SQL
• Experience and theoretical understanding in data modeling and database optimizations
• At least 3 years of proficiency in Python/Scala for data processing and transformations
• Experience with Spark, with a focus on PySpark
• Hands-on experience with main frameworks and libraries in Data Engineering domains: Spark, Kafka, Airflow, etc., with a proven record of debugging and optimization experience
• Experience with cloud-based data processing solutions on AWS/Azure

WILL BE A PLUS

• Experience with CI/CD in data engineering
• Exposure to BI tools like Tableau, Qlik, Grafana, or similar
• Databricks experience/certification

Responsibilities

• Create ETL pipelines, orchestration configurations, CI/CD automation, scripts, etc.
• Analyze, organize, and interpret raw data using a modern data stack
• Create SQL queries to efficiently manipulate data
• Contributing to and spearheading Data Engineering excellence: Research technology trends and conduct best practices analysis to ensure our solutions remain state-of-the-art