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.