Build and optimize scalable data pipelines and cloud-based data solutions using Python, PySpark, SQL, and Snowflake. Integrate REST APIs and external data sources, develop ETL/ELT workflows, optimize Snowflake queries, and implement data quality, validation, monitoring, and automation. Collaborate with engineering and analytics teams to deliver reliable data platforms.
Job Description
Data Engineer - Python, PySpark, SQL, Snowflake & API Integration
Job Description:
We are seeking a skilled Data Engineer with strong hands-on experience in Python, PySpark, SQL, Snowflake, and API integrations to build scalable data pipelines and cloud-based data solutions.
Key Responsibilities:
- Design, develop, and optimize data pipelines using Python, PySpark, SQL, and Snowflake.
- Integrate REST APIs and external data sources into Snowflake-based data platforms.
- Build and maintain ETL/ELT workflows for data ingestion, transformation, and processing.
- Develop efficient SQL queries and optimize Snowflake performance.
- Implement data quality, validation, monitoring, and automation.
- Collaborate with engineering and analytics teams to deliver reliable data solutions.
Required Qualifications:
- 3+ years of experience in Data Engineering.
- Strong hands-on expertise in Python, PySpark, SQL, and Snowflake.
- Experience with REST APIs, JSON, and API-based data integration.
- Knowledge of ETL/ELT processes, data modeling, and data warehousing.
- Experience with cloud platforms such as AWS, Azure, or GCP is preferred.
Additional Information
All your information will be kept confidential according to EEO guidelines.
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