Python Data Engineer

Design and implement the data infrastructure for a major telecommunications company serving 50+ million customers, where your pipelines will process terabytes of network data daily to optimize service quality and predict infrastructure needs. You'll build sophisticated ETL systems using Apache Airflow, Spark, and Kafka to handle real-time streaming data from cell towers, customer usage patterns, and network performance metrics. The project involves creating data lakes, implementing data quality monitoring, and building machine learning feature pipelines that feed predictive models for network optimization. You'll work closely with data scientists and network engineers to ensure data accuracy and availability while optimizing processing costs and performance. This role offers the opportunity to work with massive scale data systems while directly impacting the quality of telecommunications services for millions of users. You'll be responsible for architecting solutions that handle peak traffic loads during major events while maintaining data consistency and reliability across distributed systems.

• Design and build data processing pipelines
• Implement ETL processes for large datasets
• Optimize data workflows and performance
• Ensure data quality and reliability
• Collaborate with data scientists and analysts

• 3+ years of data engineering experience
• Strong proficiency in Python and SQL
• Experience with data pipeline orchestration tools
• Knowledge of big data processing frameworks
• Understanding of data modeling and warehousing