About the role
We are looking for a highly skilled Data Engineer to design, build, and optimize scalable data platforms and pipelines. The ideal candidate should have strong expertise in data lakes, data warehousing, SQL, and PySpark, along with excellent problem-solving abilities. Experience with AWS Redshift is a plus.
Responsibilities:
- Design and implement scalable data lake and data warehouse architectures.
- Develop and optimize complex SQL queries for ETL and data transformation.
- Build and maintain high-performance data pipelines using PySpark.
- Optimize large-scale data processing workflows for performance and scalability.
- Ensure data quality, governance, and compliance across data platforms.
- Collaborate with cross-functional teams to gather business requirements and deliver data solutions.
- Manage and optimize AWS Redshift clusters for efficient data warehousing.
Requirements:
- 5+ years of experience in data engineering.
- Strong hands-on experience with data lakes and data warehouse design and implementation.
- Advanced proficiency in SQL.
- Strong experience with PySpark for distributed data processing and ETL.
- Excellent analytical and problem-solving skills.
- Good to Have: Experience with AWS Redshift.