Key skills
AWSCloudPySparkPythonSparkSQLData EngineeringAnalyticsBIBusiness IntelligencePerformance OptimizationLeadership
About this role
Role Overview
- Design, develop, and implement data engineering solutions on AWS cloud
- Build scalable data pipelines using Spark, PySpark, and Python
- Ensure data quality, integrity, and performance optimization across data pipelines
- Collaborate with data architects and business stakeholders
- Provide technical leadership and mentorship to data engineers
Requirements
- Overall 8+ years of experience
- Lead the design, development, and implementation of data engineering solutions on AWS cloud
- Architect and build scalable data pipelines using Spark, PySpark, and Python
- Design and implement data lakes and data warehouse solutions to support analytics and reporting needs
- Develop optimized SQL queries and transformations for large-scale data processing
- Create and maintain data models (dimensional and normalized) to support business intelligence and analytics use cases
- Ensure data quality, integrity, and performance optimization across data pipelines
- Collaborate with data architects, BI teams, and business stakeholders to translate requirements into scalable data solutions
- Provide technical leadership and mentorship to data engineers
- Drive best practices in coding standards, data governance, and performance tuning
- Participate in architecture discussions, design reviews, and project planning
- Ensure timely delivery of data engineering solutions
Tech Stack
- AWS
- Cloud
- PySpark
- Python
- Spark
- SQL