Description

Key Skills: Pyspark, AWS, Data Warehouse, Azure Data lake, SQL, Python, Apache Spark

Roles and Responsibilities:

• Design and implement scalable data ingestion and transformation pipelines on AWS using PySpark and SQL.
• Build and maintain data lake and data warehouse solutions, including data modeling, partitioning, and performance tuning.
• Develop reliable ETL/ELT workflows, ensuring data quality, correctness, and consistency across downstream consumers.
• Optimize query and job performance for large datasets, including efficient storage formats and execution strategies.
• Collaborate with analytics and engineering teams to deliver datasets that meet reporting and analytics requirements.

Skills Required:

• 8-12 years of relevant experience in data engineering
• AWS (data engineering services and deployment on AWS)
• PySpark for distributed data processing
• SQL for data querying, transformations, and performance optimization
• Data Warehousing and Data Lakes for building analytics-ready storage and curated datasets

Good to Have:

• Python
• Apache Spark

Education: Bachelor's Degree in Computer Science, Master's Degree in Data Science

Key Skills

Education

Any Graduate