Data Engineer

Role Summary

The Data Engineer will design, build, and optimize large-scale data pipelines and data platforms. This role is hands-on and plays a key part in translating architectural designs into production-ready solutions.

Key Responsibilities

• Build and maintain scalable batch and streaming data pipelines
• Optimize Spark jobs for performance and reliability
• Develop and manage data models and transformations
• Ensure data quality, reliability, and observability
• Collaborate with architects to implement target architectures
• Ensure smooth deployment to higher environments
• Review code, enforce engineering standards, and mentor junior engineers
• Support production deployments and incident resolution

Core Technical Skills

• Strong experience in Spark, PySpark and Python
• Strong experience in designing and maintaining ETL pipelines.
• Experience with scheduling ETL pipelines, defining dependencies
• Experience in scheduling ETL pipelines and knowledge of Apache Airflow.
• Strong RDBMS & SQL skills
• Experience in dimensional data modelling/3NF data modelling for Data warehouses.
• Experience in implementation of Data Lakehosue/Data Lake/Data Warehouse
• Strong experience in one of the major cloud platforms. Preferably AWS, Azure.

Experience

• 410 years of experience in data engineering roles
• Exposure to product engineering backgrounds is a strong plus, with emphasis on building scalable, data-driven platforms.