Data Engineer

Role Summary

The Senior 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

- 4–10 years of experience in data engineering roles - Exposure to product engineering backgrounds is a strong plus, with emphasis on building scalable, data-driven platforms.